ARCOCT: Automatic detection of lumen border in intravascular OCT images.

PubMed

Cheimariotis, Grigorios-Aris; Chatzizisis, Yiannis S; Koutkias, Vassilis G; Toutouzas, Konstantinos; Giannopoulos, Andreas; Riga, Maria; Chouvarda, Ioanna; Antoniadis, Antonios P; Doulaverakis, Charalambos; Tsamboulatidis, Ioannis; Kompatsiaris, Ioannis; Giannoglou, George D; Maglaveras, Nicos

2017-11-01

Intravascular optical coherence tomography (OCT) is an invaluable tool for the detection of pathological features on the arterial wall and the investigation of post-stenting complications. Computational lumen border detection in OCT images is highly advantageous, since it may support rapid morphometric analysis. However, automatic detection is very challenging, since OCT images typically include various artifacts that impact image clarity, including features such as side branches and intraluminal blood presence. This paper presents ARCOCT, a segmentation method for fully-automatic detection of lumen border in OCT images. ARCOCT relies on multiple, consecutive processing steps, accounting for image preparation, contour extraction and refinement. In particular, for contour extraction ARCOCT employs the transformation of OCT images based on physical characteristics such as reflectivity and absorption of the tissue and, for contour refinement, local regression using weighted linear least squares and a 2nd degree polynomial model is employed to achieve artifact and small-branch correction as well as smoothness of the artery mesh. Our major focus was to achieve accurate contour delineation in the various types of OCT images, i.e., even in challenging cases with branches and artifacts. ARCOCT has been assessed in a dataset of 1812 images (308 from stented and 1504 from native segments) obtained from 20 patients. ARCOCT was compared against ground-truth manual segmentation performed by experts on the basis of various geometric features (e.g. area, perimeter, radius, diameter, centroid, etc.) and closed contour matching indicators (the Dice index, the Hausdorff distance and the undirected average distance), using standard statistical analysis methods. The proposed method was proven very efficient and close to the ground-truth, exhibiting non statistically-significant differences for most of the examined metrics. ARCOCT allows accurate and fully-automated lumen border detection in OCT images. Copyright © 2017 Elsevier B.V. All rights reserved.

76 FR 13204 - Agency Information Collection Activities: Automated Commercial Environment Trade Survey

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2011-03-10

... Activities: Automated Commercial Environment Trade Survey AGENCY: U.S. Customs and Border Protection (CBP... requirement concerning the: Automated Commercial Environment Trade Survey. [[Page 13205

Three-dimensional segmentation of luminal and adventitial borders in serial intravascular ultrasound images

NASA Technical Reports Server (NTRS)

Shekhar, R.; Cothren, R. M.; Vince, D. G.; Chandra, S.; Thomas, J. D.; Cornhill, J. F.

1999-01-01

Intravascular ultrasound (IVUS) provides exact anatomy of arteries, allowing accurate quantitative analysis. Automated segmentation of IVUS images is a prerequisite for routine quantitative analyses. We present a new three-dimensional (3D) segmentation technique, called active surface segmentation, which detects luminal and adventitial borders in IVUS pullback examinations of coronary arteries. The technique was validated against expert tracings by computing correlation coefficients (range 0.83-0.97) and William's index values (range 0.37-0.66). The technique was statistically accurate, robust to image artifacts, and capable of segmenting a large number of images rapidly. Active surface segmentation enabled geometrically accurate 3D reconstruction and visualization of coronary arteries and volumetric measurements.

Semi-automated discrimination of retinal pigmented epithelial cells in two-photon fluorescence images of mouse retinas.

PubMed

Alexander, Nathan S; Palczewska, Grazyna; Palczewski, Krzysztof

2015-08-01

Automated image segmentation is a critical step toward achieving a quantitative evaluation of disease states with imaging techniques. Two-photon fluorescence microscopy (TPM) has been employed to visualize the retinal pigmented epithelium (RPE) and provide images indicating the health of the retina. However, segmentation of RPE cells within TPM images is difficult due to small differences in fluorescence intensity between cell borders and cell bodies. Here we present a semi-automated method for segmenting RPE cells that relies upon multiple weak features that differentiate cell borders from the remaining image. These features were scored by a search optimization procedure that built up the cell border in segments around a nucleus of interest. With six images used as a test, our method correctly identified cell borders for 69% of nuclei on average. Performance was strongly dependent upon increasing retinosome content in the RPE. TPM image analysis has the potential of providing improved early quantitative assessments of diseases affecting the RPE.

Vision restoration therapy (VRT) efficacy as assessed by comparative perimetric analysis and subjective questionnaires.

PubMed

Sabel, Bernhard A; Kenkel, Sigrid; Kasten, Erich

2004-01-01

We wished to evaluate the efficacy of vision restoration therapy (VRT) in patients with post-chiasmatic brain damage using different functional perimetric tests. These were compared with measures of subjective vision and reaction time. An open trial was conducted with hemianopia/scotoma (n=16) patients. Before and after 6 months of VRT results of high resolution (HRP) and Tuebingen automated perimetry (TAP) were evaluated and compared to performance in a Scanning Laser Ophthalmoscope (SLO) as previously reported. Whereas TAP and HRP used above-threshold or near-threshold individual target stimuli on grey background, the SLO used a psychophysical task of detection of three black targets (reverse stimulus) on bright red, patterned background. Subjective testimonials of activities of daily living (ADL) were probed with questionnaires and interviews. Before VRT, the visual field border as assessed by SLO was located significantly closer to the vertical midline than the HRP and TAP border (border mismatch). After VRT the SLO border was still unchanged whereas HRP measurements revealed significant border shifts due to improved stimulus detection (p<0.0001) and improved reaction time (p<0.005) . Fewer misses were also observed in both eyes with TAP (p<0.01) which was primarily due to a significant shift of the absolute borders. Thus, VRT potentiated the mismatch between the SLO borders and the HRP/TAP borders. Fixation performance and the blind spot position remained unchanged after VRT. ADL ratings in the questionnaire improved significantly after VRT which was confirmed by independent patient testimonials. We replicated earlier findings that VRT improves stimulus detection in HRP and TAP perimetry which were accompanied by subjective, visual improvements. These changes are not caused by fixation or eye movement artifacts. Because the SLO border was located significantly closer to the vertical midline before VRT ("border mismatch") and, in contrast to HRP and TAP, did not change after VRT, we interpret this border mismatch to indicate that the SLO task was too difficult to perform and thus insensitive to VRT effects. Significant reaction time improvements indicate that plasticity of temporal processing might play an important role in vision restoration after brain damage. A further description of the precise psychophysical nature of the restored areas of residual vision is now warranted.

Automated measurement of stent strut coverage in intravascular optical coherence tomography

NASA Astrophysics Data System (ADS)

Ahn, Chi Young; Kim, Byeong-Keuk; Hong, Myeong-Ki; Jang, Yangsoo; Heo, Jung; Joo, Chulmin; Seo, Jin Keun

2015-02-01

Optical coherence tomography (OCT) is a non-invasive, cross-sectional imaging modality that has become a prominent imaging method in percutaneous intracoronary intervention. We present an automated detection algorithm for stent strut coordinates and coverage in OCT images. The algorithm for stent strut detection is composed of a coordinate transformation from the polar to the Cartesian domains and application of second derivative operators in the radial and the circumferential directions. Local region-based active contouring was employed to detect lumen boundaries. We applied the method to the OCT pullback images acquired from human patients in vivo to quantitatively measure stent strut coverage. The validation studies against manual expert assessments demonstrated high Pearson's coefficients ( R = 0.99) in terms of the stent strut coordinates, with no significant bias. An averaged Hausdorff distance of < 120 μm was obtained for vessel border detection. Quantitative comparison in stent strut to vessel wall distance found a bias of < 12.3 μm and a 95% confidence of < 110 μm.

76 FR 34740 - Agency Information Collection Activities: Automated Clearinghouse

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-14

... Activities: Automated Clearinghouse AGENCY: U.S. Customs and Border Protection, Department of Homeland... (OMB) for review and approval in accordance with the Paperwork Reduction Act: Automated Clearinghouse... the use of appropriate automated, electronic, mechanical, or other technological techniques or other...

Image processing techniques for noise removal, enhancement and segmentation of cartilage OCT images

NASA Astrophysics Data System (ADS)

Rogowska, Jadwiga; Brezinski, Mark E.

2002-02-01

Osteoarthritis, whose hallmark is the progressive loss of joint cartilage, is a major cause of morbidity worldwide. Recently, optical coherence tomography (OCT) has demonstrated considerable promise for the assessment of articular cartilage. Among the most important parameters to be assessed is cartilage width. However, detection of the bone cartilage interface is critical for the assessment of cartilage width. At present, the quantitative evaluations of cartilage thickness are being done using manual tracing of cartilage-bone borders. Since data is being obtained near video rate with OCT, automated identification of the bone-cartilage interface is critical. In order to automate the process of boundary detection on OCT images, there is a need for developing new image processing techniques. In this paper we describe the image processing techniques for speckle removal, image enhancement and segmentation of cartilage OCT images. In particular, this paper focuses on rabbit cartilage since this is an important animal model for testing both chondroprotective agents and cartilage repair techniques. In this study, a variety of techniques were examined. Ultimately, by combining an adaptive filtering technique with edge detection (vertical gradient, Sobel edge detection), cartilage edges can be detected. The procedure requires several steps and can be automated. Once the cartilage edges are outlined, the cartilage thickness can be measured.

A new method of edge detection for object recognition

USGS Publications Warehouse

Maddox, Brian G.; Rhew, Benjamin

2004-01-01

Traditional edge detection systems function by returning every edge in an input image. This can result in a large amount of clutter and make certain vectorization algorithms less accurate. Accuracy problems can then have a large impact on automated object recognition systems that depend on edge information. A new method of directed edge detection can be used to limit the number of edges returned based on a particular feature. This results in a cleaner image that is easier for vectorization. Vectorized edges from this process could then feed an object recognition system where the edge data would also contain information as to what type of feature it bordered.

Measuring border delay and crossing times at the US-Mexico border : final report on automated crossing and wait time measurement.

DOT National Transportation Integrated Search

2012-08-01

A pilot test implemented a radio frequency identification (RFID) system to automatically measure travel times of US-bound commercial vehicles at a selected Port of Entry (POE) on the USMexico border under long-term, real-world conditions. The init...

75 FR 5487 - Privacy Act of 1974: Implementation of Exemptions; Department of Homeland Security/U.S. Customs...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-03

...The Department of Homeland Security is issuing a final rule to amend its regulations to exempt portions of a Department of Homeland Security/U.S. Customs and Border Protection system of records entitled the, ``Department of Homeland Security/U.S. Customs and Border Protection--006 Automated Targeting System of Records'' from certain provisions of the Privacy Act. Specifically, the Department exempts portions of the Department of Homeland Security/U.S. Customs and Border Protection--006 Automated Targeting system of records from one or more provisions of the Privacy Act because of criminal, civil, and administrative enforcement requirements.

Autoblocker: a system for detecting and blocking of network scanning based on analysis of netflow data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bobyshev, A.; Lamore, D.; Demar, P.

2004-12-01

In a large campus network, such at Fermilab, with tens of thousands of nodes, scanning initiated from either outside of or within the campus network raises security concerns. This scanning may have very serious impact on network performance, and even disrupt normal operation of many services. In this paper we introduce a system for detecting and automatic blocking excessive traffic of different kinds of scanning, DoS attacks, virus infected computers. The system, called AutoBlocker, is a distributed computing system based on quasi-real time analysis of network flow data collected from the border router and core switches. AutoBlocker also has anmore » interface to accept alerts from IDS systems (e.g. BRO, SNORT) that are based on other technologies. The system has multiple configurable alert levels for the detection of anomalous behavior and configurable trigger criteria for automated blocking of scans at the core or border routers. It has been in use at Fermilab for about 2 years, and has become a very valuable tool to curtail scan activity within the Fermilab campus network.« less

Evaluation of training nurses to perform semi-automated three-dimensional left ventricular ejection fraction using a customised workstation-based training protocol.

PubMed

Guppy-Coles, Kristyan B; Prasad, Sandhir B; Smith, Kym C; Hillier, Samuel; Lo, Ada; Atherton, John J

2015-06-01

We aimed to determine the feasibility of training cardiac nurses to evaluate left ventricular function utilising a semi-automated, workstation-based protocol on three dimensional echocardiography images. Assessment of left ventricular function by nurses is an attractive concept. Recent developments in three dimensional echocardiography coupled with border detection assistance have reduced inter- and intra-observer variability and analysis time. This could allow abbreviated training of nurses to assess cardiac function. A comparative, diagnostic accuracy study evaluating left ventricular ejection fraction assessment utilising a semi-automated, workstation-based protocol performed by echocardiography-naïve nurses on previously acquired three dimensional echocardiography images. Nine cardiac nurses underwent two brief lectures about cardiac anatomy, physiology and three dimensional left ventricular ejection fraction assessment, before a hands-on demonstration in 20 cases. We then selected 50 cases from our three dimensional echocardiography library based on optimal image quality with a broad range of left ventricular ejection fractions, which was quantified by two experienced sonographers and the average used as the comparator for the nurses. Nurses independently measured three dimensional left ventricular ejection fraction using the Auto lvq package with semi-automated border detection. The left ventricular ejection fraction range was 25-72% (70% with a left ventricular ejection fraction <55%). All nurses showed excellent agreement with the sonographers. Minimal intra-observer variability was noted on both short-term (same day) and long-term (>2 weeks later) retest. It is feasible to train nurses to measure left ventricular ejection fraction utilising a semi-automated, workstation-based protocol on previously acquired three dimensional echocardiography images. Further study is needed to determine the feasibility of training nurses to acquire three dimensional echocardiography images on real-world patients to measure left ventricular ejection fraction. Nurse-performed evaluation of left ventricular function could facilitate the broader application of echocardiography to allow cost-effective screening and monitoring for left ventricular dysfunction in high-risk populations. © 2014 John Wiley & Sons Ltd.

Optical techniques: using coarse and detailed scans for the preventive acquisition of fingerprints with chromatic white-light sensors

NASA Astrophysics Data System (ADS)

Hildebrandt, Mario; Dittmann, Jana; Vielhauer, Claus; Leich, Marcus

2011-11-01

The preventive application of automated latent fingerprint acquisition devices can enhance the Homeland Defence, e.g. by improving the border security. Here, contact-less optical acquisition techniques for the capture of traces are subject to research; chromatic white light sensors allow for multi-mode operation using coarse or detailed scans. The presence of potential fingerprints could be detected using fast coarse scans. Those Regions-of- Interest can be acquired afterwards with high-resolution detailed scans to allow for a verification or identification of individuals. An acquisition and analysis of fingerprint traces on different objects that are imported or pass borders might be a great enhancement for security. Additionally, if suspicious objects require a further investigation, an initial securing of potential fingerprints could be very useful. In this paper we show current research results for the coarse detection of fingerprints to prepare the detailed acquisition from various surface materials that are relevant for preventive applications.

Effort to test, evaluate and deploy technologies to automate the measurement of real-time border wait times at United States-Canada land border crossings.

DOT National Transportation Integrated Search

2011-09-01

The United States and Canada share the largest bi-national trading relationship in the world. An efficient and cost-effective border crossing system for both freight and passenger vehicle traffic is thus vital to the economic well-being and security ...

Automated image alignment and segmentation to follow progression of geographic atrophy in age-related macular degeneration.

PubMed

Ramsey, David J; Sunness, Janet S; Malviya, Poorva; Applegate, Carol; Hager, Gregory D; Handa, James T

2014-07-01

To develop a computer-based image segmentation method for standardizing the quantification of geographic atrophy (GA). The authors present an automated image segmentation method based on the fuzzy c-means clustering algorithm for the detection of GA lesions. The method is evaluated by comparing computerized segmentation against outlines of GA drawn by an expert grader for a longitudinal series of fundus autofluorescence images with paired 30° color fundus photographs for 10 patients. The automated segmentation method showed excellent agreement with an expert grader for fundus autofluorescence images, achieving a performance level of 94 ± 5% sensitivity and 98 ± 2% specificity on a per-pixel basis for the detection of GA area, but performed less well on color fundus photographs with a sensitivity of 47 ± 26% and specificity of 98 ± 2%. The segmentation algorithm identified 75 ± 16% of the GA border correctly in fundus autofluorescence images compared with just 42 ± 25% for color fundus photographs. The results of this study demonstrate a promising computerized segmentation method that may enhance the reproducibility of GA measurement and provide an objective strategy to assist an expert in the grading of images.

77 FR 14535 - Agency Information Collection Activities: Application To Use the Automated Commercial Environment...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-12

... Activities: Application To Use the Automated Commercial Environment (ACE) AGENCY: U.S. Customs and Border... Commercial Environment (ACE). This request for comment is being made pursuant to the Paperwork Reduction Act... Number: None. Abstract: The Automated Commercial Environment (ACE) is a trade processing system that will...

Automated contour detection in X-ray left ventricular angiograms using multiview active appearance models and dynamic programming.

PubMed

Oost, Elco; Koning, Gerhard; Sonka, Milan; Oemrawsingh, Pranobe V; Reiber, Johan H C; Lelieveldt, Boudewijn P F

2006-09-01

This paper describes a new approach to the automated segmentation of X-ray left ventricular (LV) angiograms, based on active appearance models (AAMs) and dynamic programming. A coupling of shape and texture information between the end-diastolic (ED) and end-systolic (ES) frame was achieved by constructing a multiview AAM. Over-constraining of the model was compensated for by employing dynamic programming, integrating both intensity and motion features in the cost function. Two applications are compared: a semi-automatic method with manual model initialization, and a fully automatic algorithm. The first proved to be highly robust and accurate, demonstrating high clinical relevance. Based on experiments involving 70 patient data sets, the algorithm's success rate was 100% for ED and 99% for ES, with average unsigned border positioning errors of 0.68 mm for ED and 1.45 mm for ES. Calculated volumes were accurate and unbiased. The fully automatic algorithm, with intrinsically less user interaction was less robust, but showed a high potential, mostly due to a controlled gradient descent in updating the model parameters. The success rate of the fully automatic method was 91% for ED and 83% for ES, with average unsigned border positioning errors of 0.79 mm for ED and 1.55 mm for ES.

Automatic lesion boundary detection in dermoscopy images using gradient vector flow snakes

PubMed Central

Erkol, Bulent; Moss, Randy H.; Stanley, R. Joe; Stoecker, William V.; Hvatum, Erik

2011-01-01

Background Malignant melanoma has a good prognosis if treated early. Dermoscopy images of pigmented lesions are most commonly taken at × 10 magnification under lighting at a low angle of incidence while the skin is immersed in oil under a glass plate. Accurate skin lesion segmentation from the background skin is important because some of the features anticipated to be used for diagnosis deal with shape of the lesion and others deal with the color of the lesion compared with the color of the surrounding skin. Methods In this research, gradient vector flow (GVF) snakes are investigated to find the border of skin lesions in dermoscopy images. An automatic initialization method is introduced to make the skin lesion border determination process fully automated. Results Skin lesion segmentation results are presented for 70 benign and 30 melanoma skin lesion images for the GVF-based method and a color histogram analysis technique. The average errors obtained by the GVF-based method are lower for both the benign and melanoma image sets than for the color histogram analysis technique based on comparison with manually segmented lesions determined by a dermatologist. Conclusions The experimental results for the GVF-based method demonstrate promise as an automated technique for skin lesion segmentation in dermoscopy images. PMID:15691255

76 FR 28801 - Agency Information Collection Activities: Automated Commercial Environment Trade Survey

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2011-05-18

... Activities: Automated Commercial Environment Trade Survey AGENCY: U.S. Customs and Border Protection... Environment Trade Survey. This document is published to obtain comments from the public and affected agencies... Environment Trade Survey. OMB Number: Will be assigned upon approval. Form Number: None. Abstract: CBP plans...

21 CFR 1.280 - How must you submit prior notice?

Code of Federal Regulations, 2011 CFR

2011-04-01

... through: (1) The U.S. Customs and Border Protection (CBP) Automated Broker Interface of the Automated... through the FDA Prior Notice System Interface (FDA PNSI) for articles of food imported or offered for... system is not working or if the ABI/ACS interface is not working, prior notice must be submitted through...

Exploiting unsupervised and supervised classification for segmentation of the pathological lung in CT

NASA Astrophysics Data System (ADS)

Korfiatis, P.; Kalogeropoulou, C.; Daoussis, D.; Petsas, T.; Adonopoulos, A.; Costaridou, L.

2009-07-01

Delineation of lung fields in presence of diffuse lung diseases (DLPDs), such as interstitial pneumonias (IP), challenges segmentation algorithms. To deal with IP patterns affecting the lung border an automated image texture classification scheme is proposed. The proposed segmentation scheme is based on supervised texture classification between lung tissue (normal and abnormal) and surrounding tissue (pleura and thoracic wall) in the lung border region. This region is coarsely defined around an initial estimate of lung border, provided by means of Markov Radom Field modeling and morphological operations. Subsequently, a support vector machine classifier was trained to distinguish between the above two classes of tissue, using textural feature of gray scale and wavelet domains. 17 patients diagnosed with IP, secondary to connective tissue diseases were examined. Segmentation performance in terms of overlap was 0.924±0.021, and for shape differentiation mean, rms and maximum distance were 1.663±0.816, 2.334±1.574 and 8.0515±6.549 mm, respectively. An accurate, automated scheme is proposed for segmenting abnormal lung fields in HRC affected by IP

Optimal Deployment of Unmanned Aerial Vehicles for Border Surveillance

DTIC Science & Technology

2014-06-01

and intercept intruders that are trying to trespass a border. These intruders can include terrorists, drug traffickers, smugglers, illegal immigrants...routes, altitudes, and speeds in order to maximize the probability of detecting intruders trying to trespass a given border. These models will...Border surveillance is an important concern for most nations wanting to detect and intercept intruders that are trying to trespass a border. These

Automated Border Control Systems as Part of e-border Crossing Process

DTIC Science & Technology

2015-01-01

which is led by Defence Research and Development Canada’s Centre for Security Science, in partnership with Public Safety Canada. The project was led...Canada, as represented by the Minister of National Defence, 2015 © Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de...FAST US,EU (2013): AVATAR kiosks Examples: US, Canada: Deployed in Vancouver, Montreal, Toronto, and Chicago International Airports

Impact of various color LED flashlights and different lighting source to skin distances on the manual and the computer-aided detection of basal cell carcinoma borders.

PubMed

Bakht, Mohamadreza K; Pouladian, Majid; Mofrad, Farshid B; Honarpisheh, Hamid

2014-02-01

Quantitative analysis based on digital skin image has been proven to be helpful in dermatology. Moreover, the borders of the basal cell carcinoma (BCC) lesions have been challenging borders for the automatic detection methods. In this work, a computer-aided dermatoscopy system was proposed to enhance the clinical detection of BCC lesion borders. Fifty cases of BCC were selected and 2000 pictures were taken. The lesion images data were obtained with eight colors of flashlights and in five different lighting source to skin distances (SSDs). Then, the image-processing techniques were used for automatic detection of lesion borders. Further, the dermatologists marked the lesions on the obtained photos. Considerable differences between the obtained values referring to the photographs that were taken at super blue and aqua green color lighting were observed for most of the BCC borders. It was observed that by changing the SSD, an optimum distance could be found where that the accuracy of the detection reaches to a maximum value. This study clearly indicates that by changing SSD and lighting color, manual and automatic detection of BCC lesions borders can be enhanced. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A landsat data tiling and compositing approach optimized for change detection in the conterminous United States

USGS Publications Warehouse

Nelson, Kurtis; Steinwand, Daniel R.

2015-01-01

Annual disturbance maps are produced by the LANDFIRE program across the conterminous United States (CONUS). Existing LANDFIRE disturbance data from 1999 to 2010 are available and current efforts will produce disturbance data through 2012. A tiling and compositing approach was developed to produce bi-annual images optimized for change detection. A tiled grid of 10,000 × 10,000 30 m pixels was defined for CONUS and adjusted to consolidate smaller tiles along national borders, resulting in 98 non-overlapping tiles. Data from Landsat-5,-7, and -8 were re-projected to the tile extents, masked to remove clouds, shadows, water, and snow/ice, then composited using a cosine similarity approach. The resultant images were used in a change detection algorithm to determine areas of vegetation change. This approach enabled more efficient processing compared to using single Landsat scenes, by taking advantage of overlap between adjacent paths, and allowed an automated system to be developed for the entire process.

Automated brainstem co-registration (ABC) for MRI.

PubMed

Napadow, Vitaly; Dhond, Rupali; Kennedy, David; Hui, Kathleen K S; Makris, Nikos

2006-09-01

Group data analysis in brainstem neuroimaging is predicated on accurate co-registration of anatomy. As the brainstem is comprised of many functionally heterogeneous nuclei densely situated adjacent to one another, relatively small errors in co-registration can manifest in increased variance or decreased sensitivity (or significance) in detecting activations. We have devised a 2-stage automated, reference mask guided registration technique (Automated Brainstem Co-registration, or ABC) for improved brainstem co-registration. Our approach utilized a brainstem mask dataset to weight an automated co-registration cost function. Our method was validated through measurement of RMS error at 12 manually defined landmarks. These landmarks were also used as guides for a secondary manual co-registration option, intended for outlier individuals that may not adequately co-register with our automated method. Our methodology was tested on 10 healthy human subjects and compared to traditional co-registration techniques (Talairach transform and automated affine transform to the MNI-152 template). We found that ABC had a significantly lower mean RMS error (1.22 +/- 0.39 mm) than Talairach transform (2.88 +/- 1.22 mm, mu +/- sigma) and the global affine (3.26 +/- 0.81 mm) method. Improved accuracy was also found for our manual-landmark-guided option (1.51 +/- 0.43 mm). Visualizing individual brainstem borders demonstrated more consistent and uniform overlap for ABC compared to traditional global co-registration techniques. Improved robustness (lower susceptibility to outliers) was demonstrated with ABC through lower inter-subject RMS error variance compared with traditional co-registration methods. The use of easily available and validated tools (AFNI and FSL) for this method should ease adoption by other investigators interested in brainstem data group analysis.

Evaluation of cell count and classification capabilities in body fluids using a fully automated Sysmex XN equipped with high-sensitive Analysis (hsA) mode and DI-60 hematology analyzer system.

PubMed

Takemura, Hiroyuki; Ai, Tomohiko; Kimura, Konobu; Nagasaka, Kaori; Takahashi, Toshihiro; Tsuchiya, Koji; Yang, Haeun; Konishi, Aya; Uchihashi, Kinya; Horii, Takashi; Tabe, Yoko; Ohsaka, Akimichi

2018-01-01

The XN series automated hematology analyzer has been equipped with a body fluid (BF) mode to count and differentiate leukocytes in BF samples including cerebrospinal fluid (CSF). However, its diagnostic accuracy is not reliable for CSF samples with low cell concentration at the border between normal and pathologic level. To overcome this limitation, a new flow cytometry-based technology, termed "high sensitive analysis (hsA) mode," has been developed. In addition, the XN series analyzer has been equipped with the automated digital cell imaging analyzer DI-60 to classify cell morphology including normal leukocytes differential and abnormal malignant cells detection. Using various BF samples, we evaluated the performance of the XN-hsA mode and DI-60 compared to manual microscopic examination. The reproducibility of the XN-hsA mode showed good results in samples with low cell densities (coefficient of variation; % CV: 7.8% for 6 cells/μL). The linearity of the XN-hsA mode was established up to 938 cells/μL. The cell number obtained using the XN-hsA mode correlated highly with the corresponding microscopic examination. Good correlation was also observed between the DI-60 analyses and manual microscopic classification for all leukocyte types, except monocytes. In conclusion, the combined use of cell counting with the XN-hsA mode and automated morphological analyses using the DI-60 mode is potentially useful for the automated analysis of BF cells.

75 FR 37823 - Notice of Meeting of the Advisory Committee on Commercial Operations of Customs and Border...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-30

... Subcommittee. 6. Automation Subcommittee. 7. Global Supply Chain Security Subcommittee. 8. Bond Subcommittee... Individuals With Disabilities For information on facilities or services for individuals with disabilities or...

Feasibility study of the automated detection and localization of underground tunnel excavation using Brillouin optical time domain reflectometer

NASA Astrophysics Data System (ADS)

Klar, Assaf; Linker, Raphael

2009-05-01

Cross-borders smuggling tunnels enable unmonitored movement of people, drugs and weapons and pose a very serious threat to homeland security. Recent advances in strain measurements using optical fibers allow the development of smart underground security fences that could detect the excavation of smuggling tunnels. This paper presents the first stages in the development of such a fence using Brillouin Optical Time Domain Reflectometry (BOTDR). In the simulation study, two different ground displacement models are used in order to evaluate the robustness of the system against imperfect modeling. In both cases, soil-fiber interaction is considered. Measurement errors, and surface disturbances (obtained from a field test) are also included in the calibration and validation stages of the system. The proposed detection system is based on wavelet decomposition of the BOTDR signal, followed by a neural network that is trained to recognize the tunnel signature in the wavelet coefficients. The results indicate that the proposed system is capable of detecting even small tunnel (0.5m diameter) as deep as 20 meter.

Automated carotid artery intima layer regional segmentation.

PubMed

Meiburger, Kristen M; Molinari, Filippo; Acharya, U Rajendra; Saba, Luca; Rodrigues, Paulo; Liboni, William; Nicolaides, Andrew; Suri, Jasjit S

2011-07-07

Evaluation of the carotid artery wall is essential for the assessment of a patient's cardiovascular risk or for the diagnosis of cardiovascular pathologies. This paper presents a new, completely user-independent algorithm called carotid artery intima layer regional segmentation (CAILRS, a class of AtheroEdge™ systems), which automatically segments the intima layer of the far wall of the carotid ultrasound artery based on mean shift classification applied to the far wall. Further, the system extracts the lumen-intima and media-adventitia borders in the far wall of the carotid artery. Our new system is characterized and validated by comparing CAILRS borders with the manual tracings carried out by experts. The new technique is also benchmarked with a semi-automatic technique based on a first-order absolute moment edge operator (FOAM) and compared to our previous edge-based automated methods such as CALEX (Molinari et al 2010 J. Ultrasound Med. 29 399-418, 2010 IEEE Trans. Ultrason. Ferroelectr. Freq. Control 57 1112-24), CULEX (Delsanto et al 2007 IEEE Trans. Instrum. Meas. 56 1265-74, Molinari et al 2010 IEEE Trans. Ultrason. Ferroelectr. Freq. Control 57 1112-24), CALSFOAM (Molinari et al Int. Angiol. (at press)), and CAUDLES-EF (Molinari et al J. Digit. Imaging (at press)). Our multi-institutional database consisted of 300 longitudinal B-mode carotid images. In comparison to semi-automated FOAM, CAILRS showed the IMT bias of -0.035 ± 0.186 mm while FOAM showed -0.016 ± 0.258 mm. Our IMT was slightly underestimated with respect to the ground truth IMT, but showed uniform behavior over the entire database. CAILRS outperformed all the four previous automated methods. The system's figure of merit was 95.6%, which was lower than that of the semi-automated method (98%), but higher than that of the other automated techniques.

Automated carotid artery intima layer regional segmentation

NASA Astrophysics Data System (ADS)

Meiburger, Kristen M.; Molinari, Filippo; Rajendra Acharya, U.; Saba, Luca; Rodrigues, Paulo; Liboni, William; Nicolaides, Andrew; Suri, Jasjit S.

2011-07-01

Evaluation of the carotid artery wall is essential for the assessment of a patient's cardiovascular risk or for the diagnosis of cardiovascular pathologies. This paper presents a new, completely user-independent algorithm called carotid artery intima layer regional segmentation (CAILRS, a class of AtheroEdge™ systems), which automatically segments the intima layer of the far wall of the carotid ultrasound artery based on mean shift classification applied to the far wall. Further, the system extracts the lumen-intima and media-adventitia borders in the far wall of the carotid artery. Our new system is characterized and validated by comparing CAILRS borders with the manual tracings carried out by experts. The new technique is also benchmarked with a semi-automatic technique based on a first-order absolute moment edge operator (FOAM) and compared to our previous edge-based automated methods such as CALEX (Molinari et al 2010 J. Ultrasound Med. 29 399-418, 2010 IEEE Trans. Ultrason. Ferroelectr. Freq. Control 57 1112-24), CULEX (Delsanto et al 2007 IEEE Trans. Instrum. Meas. 56 1265-74, Molinari et al 2010 IEEE Trans. Ultrason. Ferroelectr. Freq. Control 57 1112-24), CALSFOAM (Molinari et al Int. Angiol. (at press)), and CAUDLES-EF (Molinari et al J. Digit. Imaging (at press)). Our multi-institutional database consisted of 300 longitudinal B-mode carotid images. In comparison to semi-automated FOAM, CAILRS showed the IMT bias of -0.035 ± 0.186 mm while FOAM showed -0.016 ± 0.258 mm. Our IMT was slightly underestimated with respect to the ground truth IMT, but showed uniform behavior over the entire database. CAILRS outperformed all the four previous automated methods. The system's figure of merit was 95.6%, which was lower than that of the semi-automated method (98%), but higher than that of the other automated techniques.

Volpe engineers use biometrics to help ease border crush

DOT National Transportation Integrated Search

1997-01-01

Using technology previously reserved for military and other high security applications, engineers from the Safety and Security Systems Division of the Volpe Center have developed a number of automated biometric systems to speed the processing of freq...

Interferon Gamma-Based Detection of Latent Tuberculosis Infection in the Border States of Nuevo Leon and Tamaulipas, Mexico

PubMed Central

Oren, Eyal; Alatorre-Izaguirre, Gabriela; Vargas-Villarreal, Javier; Moreno-Treviño, Maria Guadalupe; Garcialuna-Martinez, Javier; Gonzalez-Salazar, Francisco

2015-01-01

Nearly one-third of the world’s population is infected with latent tuberculosis (LTBI). Tuberculosis (TB) rates in the border states are higher than national rates in both the US and Mexico, with the border accounting for 30% of total registered TB cases in both countries. However, LTBI rates in the general population in Mexican border states are unknown. In this region, LTBI is diagnosed using the tuberculin skin test (TST). New methods of detection more specific than TST have been developed, although there is currently no gold standard for LTBI detection. Our objective is to demonstrate utility of the Quantiferon TB gold In-Tube (QFT-GIT) test compared with the TST to detect LTBI among border populations. This is an observational, cross-sectional study carried out in border areas of the states of Nuevo Leon and Tamaulipas, Mexico. Participants (n = 210) provided a TST and blood sample for the QFT-GIT. Kappa coefficients assessed the agreement between TST and QFT-GIT. Participant characteristics were compared using Fisher exact tests. Thirty-eight percent of participants were diagnosed with LTBI by QFT-GIT. The proportion of LTBI detected using QFT-GIT was almost double [38% (79/210)] that found by TST [19% (39/210)] (P < 0.001). Concordance between TST and QFT-GIT was low (kappa = 0.37). We recommend further studies utilizing the QFT-GIT test to detect LTBI among border populations. PMID:26484340

Interferon Gamma-Based Detection of Latent Tuberculosis Infection in the Border States of Nuevo Leon and Tamaulipas, Mexico.

PubMed

Oren, Eyal; Alatorre-Izaguirre, Gabriela; Vargas-Villarreal, Javier; Moreno-Treviño, Maria Guadalupe; Garcialuna-Martinez, Javier; Gonzalez-Salazar, Francisco

2015-01-01

Nearly one-third of the world's population is infected with latent tuberculosis (LTBI). Tuberculosis (TB) rates in the border states are higher than national rates in both the US and Mexico, with the border accounting for 30% of total registered TB cases in both countries. However, LTBI rates in the general population in Mexican border states are unknown. In this region, LTBI is diagnosed using the tuberculin skin test (TST). New methods of detection more specific than TST have been developed, although there is currently no gold standard for LTBI detection. Our objective is to demonstrate utility of the Quantiferon TB gold In-Tube (QFT-GIT) test compared with the TST to detect LTBI among border populations. This is an observational, cross-sectional study carried out in border areas of the states of Nuevo Leon and Tamaulipas, Mexico. Participants (n = 210) provided a TST and blood sample for the QFT-GIT. Kappa coefficients assessed the agreement between TST and QFT-GIT. Participant characteristics were compared using Fisher exact tests. Thirty-eight percent of participants were diagnosed with LTBI by QFT-GIT. The proportion of LTBI detected using QFT-GIT was almost double [38% (79/210)] that found by TST [19% (39/210)] (P < 0.001). Concordance between TST and QFT-GIT was low (kappa = 0.37). We recommend further studies utilizing the QFT-GIT test to detect LTBI among border populations.

Optical benchmarking of security document readers for automated border control

NASA Astrophysics Data System (ADS)

Valentín, Kristián.; Wild, Peter; Å tolc, Svorad; Daubner, Franz; Clabian, Markus

2016-10-01

Authentication and optical verification of travel documents upon crossing borders is of utmost importance for national security. Understanding the workflow and different approaches to ICAO 9303 travel document scanning in passport readers, as well as highlighting normalization issues and designing new methods to achieve better harmonization across inspection devices are key steps for the development of more effective and efficient next- generation passport inspection. This paper presents a survey of state-of-the-art document inspection systems, showcasing results of a document reader challenge investigating 9 devices with regards to optical characteristics.

An Automated Directed Spectral Search Methodology for Small Target Detection

NASA Astrophysics Data System (ADS)

Grossman, Stanley I.

Much of the current efforts in remote sensing tackle macro-level problems such as determining the extent of wheat in a field, the general health of vegetation or the extent of mineral deposits in an area. However, for many of the remaining remote sensing challenges being studied currently, such as border protection, drug smuggling, treaty verification, and the war on terror, most targets are very small in nature - a vehicle or even a person. While in typical macro-level problems the objective vegetation is in the scene, for small target detection problems it is not usually known if the desired small target even exists in the scene, never mind finding it in abundance. The ability to find specific small targets, such as vehicles, typifies this problem. Complicating the analyst's life, the growing number of available sensors is generating mountains of imagery outstripping the analysts' ability to visually peruse them. This work presents the important factors influencing spectral exploitation using multispectral data and suggests a different approach to small target detection. The methodology of directed search is presented, including the use of scene-modeled spectral libraries, various search algorithms, and traditional statistical and ROC curve analysis. The work suggests a new metric to calibrate analysis labeled the analytic sweet spot as well as an estimation method for identifying the sweet spot threshold for an image. It also suggests a new visualization aid for highlighting the target in its entirety called nearest neighbor inflation (NNI). It brings these all together to propose that these additions to the target detection arena allow for the construction of a fully automated target detection scheme. This dissertation next details experiments to support the hypothesis that the optimum detection threshold is the analytic sweet spot and that the estimation method adequately predicts it. Experimental results and analysis are presented for the proposed directed search techniques of spectral image based small target detection. It offers evidence of the functionality of the NNI visualization and also provides evidence that the increased spectral dimensionality of the 8-band Worldview-2 datasets provides noteworthy improvement in results over traditional 4-band multispectral datasets. The final experiment presents the results from a prototype fully automated target detection scheme in support of the overarching premise. This work establishes the analytic sweet spot as the optimum threshold defined as the point where error detection rate curves -- false detections vs. missing detections -- cross. At this point the errors are minimized while the detection rate is maximized. It then demonstrates that taking the first moment statistic of the histogram of calculated target detection values from a detection search with test threshold set arbitrarily high will estimate the analytic sweet spot for that image. It also demonstrates that directed search techniques -- when utilized with appropriate scene-specific modeled signatures and atmospheric compensations -- perform at least as well as in-scene search techniques 88% of the time and grossly under-performing only 11% of the time; the in-scene only performs as well or better 50% of the time. It further demonstrates the clear advantage increased multispectral dimensionality brings to detection searches improving performance in 50% of the cases while performing at least as well 72% of the time. Lastly, it presents evidence that a fully automated prototype performs as anticipated laying the groundwork for further research into fully automated processes for small target detection.

76 FR 28801 - Agency Information Collection Activities: Bonded Warehouse Regulations

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-18

... Activities: Bonded Warehouse Regulations AGENCY: U.S. Customs and Border Protection, Department of Homeland... (OMB) for review and approval in accordance with the Paperwork Reduction Act: Bonded Warehouse... appropriate automated, electronic, mechanical, or other technological techniques or other forms of information...

An artificial neural network method for lumen and media-adventitia border detection in IVUS.

PubMed

Su, Shengran; Hu, Zhenghui; Lin, Qiang; Hau, William Kongto; Gao, Zhifan; Zhang, Heye

2017-04-01

Intravascular ultrasound (IVUS) has been well recognized as one powerful imaging technique to evaluate the stenosis inside the coronary arteries. The detection of lumen border and media-adventitia (MA) border in IVUS images is the key procedure to determine the plaque burden inside the coronary arteries, but this detection could be burdensome to the doctor because of large volume of the IVUS images. In this paper, we use the artificial neural network (ANN) method as the feature learning algorithm for the detection of the lumen and MA borders in IVUS images. Two types of imaging information including spatial, neighboring features were used as the input data to the ANN method, and then the different vascular layers were distinguished accordingly through two sparse auto-encoders and one softmax classifier. Another ANN was used to optimize the result of the first network. In the end, the active contour model was applied to smooth the lumen and MA borders detected by the ANN method. The performance of our approach was compared with the manual drawing method performed by two IVUS experts on 461 IVUS images from four subjects. Results showed that our approach had a high correlation and good agreement with the manual drawing results. The detection error of the ANN method close to the error between two groups of manual drawing result. All these results indicated that our proposed approach could efficiently and accurately handle the detection of lumen and MA borders in the IVUS images. Copyright © 2016 Elsevier Ltd. All rights reserved.

Automatic detection of the breast border and nipple position on digital mammograms using genetic algorithm for asymmetry approach to detection of microcalcifications.

PubMed

Karnan, M; Thangavel, K

2007-07-01

The presence of microcalcifications in breast tissue is one of the most incident signs considered by radiologist for an early diagnosis of breast cancer, which is one of the most common forms of cancer among women. In this paper, the Genetic Algorithm (GA) is proposed for automatic look at commonly prone area the breast border and nipple position to discover the suspicious regions on digital mammograms based on asymmetries between left and right breast image. The basic idea of the asymmetry approach is to scan left and right images are subtracted to extract the suspicious region. The proposed system consists of two steps: First, the mammogram images are enhanced using median filter, normalize the image, at the pectoral muscle region is excluding the border of the mammogram and comparing for both left and right images from the binary image. Further GA is applied to magnify the detected border. The figure of merit is calculated to evaluate whether the detected border is exact or not. And the nipple position is identified using GA. The some comparisons method is adopted for detection of suspected area. Second, using the border points and nipple position as the reference the mammogram images are aligned and subtracted to extract the suspicious region. The algorithms are tested on 114 abnormal digitized mammograms from Mammogram Image Analysis Society database.

77 FR 26024 - Agency Information Collection Activities: Bonded Warehouse Proprietor's Submission

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-02

... Activities: Bonded Warehouse Proprietor's Submission AGENCY: U.S. Customs and Border Protection, Department... Budget (OMB) for review and approval in accordance with the Paperwork Reduction Act: Bonded Warehouse... information on those who are to respond, including the use of appropriate automated, electronic, mechanical...

19 CFR 143.4 - Confidentiality of data.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 19 Customs Duties 2 2011-04-01 2011-04-01 false Confidentiality of data. 143.4 Section 143.4 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) SPECIAL ENTRY PROCEDURES Automated Broker Interface § 143.4 Confidentiality of data...

Automated analysis of non-mass-enhancing lesions in breast MRI based on morphological, kinetic, and spatio-temporal moments and joint segmentation-motion compensation technique

NASA Astrophysics Data System (ADS)

Hoffmann, Sebastian; Shutler, Jamie D.; Lobbes, Marc; Burgeth, Bernhard; Meyer-Bäse, Anke

2013-12-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) represents an established method for the detection and diagnosis of breast lesions. While mass-like enhancing lesions can be easily categorized according to the Breast Imaging Reporting and Data System (BI-RADS) MRI lexicon, a majority of diagnostically challenging lesions, the so called non-mass-like enhancing lesions, remain both qualitatively as well as quantitatively difficult to analyze. Thus, the evaluation of kinetic and/or morphological characteristics of non-masses represents a challenging task for an automated analysis and is of crucial importance for advancing current computer-aided diagnosis (CAD) systems. Compared to the well-characterized mass-enhancing lesions, non-masses have no well-defined and blurred tumor borders and a kinetic behavior that is not easily generalizable and thus discriminative for malignant and benign non-masses. To overcome these difficulties and pave the way for novel CAD systems for non-masses, we will evaluate several kinetic and morphological descriptors separately and a novel technique, the Zernike velocity moments, to capture the joint spatio-temporal behavior of these lesions, and additionally consider the impact of non-rigid motion compensation on a correct diagnosis.

Feasibility of rapid and automated importation of 3D echocardiographic left ventricular (LV) geometry into a finite element (FEM) analysis model

PubMed Central

Verhey, Janko F; Nathan, Nadia S

2004-01-01

Background Finite element method (FEM) analysis for intraoperative modeling of the left ventricle (LV) is presently not possible. Since 3D structural data of the LV is now obtainable using standard transesophageal echocardiography (TEE) devices intraoperatively, the present study describes a method to transfer this data into a commercially available FEM analysis system: ABAQUS©. Methods In this prospective study TomTec LV Analysis TEE© Software was used for semi-automatic endocardial border detection, reconstruction, and volume-rendering of the clinical 3D echocardiographic data. A newly developed software program MVCP FemCoGen©, written in Delphi, reformats the TomTec file structures in five patients for use in ABAQUS and allows visualization of regional deformation of the LV. Results This study demonstrates that a fully automated importation of 3D TEE data into FEM modeling is feasible and can be efficiently accomplished in the operating room. Conclusion For complete intraoperative 3D LV finite element analysis, three input elements are necessary: 1. time-gaited, reality-based structural information, 2. continuous LV pressure and 3. instantaneous tissue elastance. The first of these elements is now available using the methods presented herein. PMID:15473901

19 CFR 192.11 - Description of the AES.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 19 Customs Duties 2 2010-04-01 2010-04-01 false Description of the AES. 192.11 Section 192.11 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) EXPORT CONTROL Filing of Export Information Through the Automated Export System (AES...

19 CFR 143.7 - Revocation of ABI participation.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 19 Customs Duties 2 2011-04-01 2011-04-01 false Revocation of ABI participation. 143.7 Section 143.7 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) SPECIAL ENTRY PROCEDURES Automated Broker Interface § 143.7 Revocation of ABI...

19 CFR 143.8 - Appeal of suspension or revocation.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 19 Customs Duties 2 2011-04-01 2011-04-01 false Appeal of suspension or revocation. 143.8 Section 143.8 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) SPECIAL ENTRY PROCEDURES Automated Broker Interface § 143.8 Appeal of...

19 CFR 143.3 - Action on application.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 19 Customs Duties 2 2011-04-01 2011-04-01 false Action on application. 143.3 Section 143.3 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) SPECIAL ENTRY PROCEDURES Automated Broker Interface § 143.3 Action on application. (a) Approval...

19 CFR 143.6 - Failure to maintain performance standards.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 19 Customs Duties 2 2011-04-01 2011-04-01 false Failure to maintain performance standards. 143.6 Section 143.6 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) SPECIAL ENTRY PROCEDURES Automated Broker Interface § 143.6 Failure to...

19 CFR 181.12 - Maintenance and availability of records.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 19 Customs Duties 2 2011-04-01 2011-04-01 false Maintenance and availability of records. 181.12 Section 181.12 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY... or in automated record storage devices (for example, magnetic discs and tapes) if associated computer...

19 CFR 181.12 - Maintenance and availability of records.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 19 Customs Duties 2 2013-04-01 2013-04-01 false Maintenance and availability of records. 181.12 Section 181.12 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY... or in automated record storage devices (for example, magnetic discs and tapes) if associated computer...

19 CFR 181.12 - Maintenance and availability of records.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 19 Customs Duties 2 2012-04-01 2012-04-01 false Maintenance and availability of records. 181.12 Section 181.12 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY... or in automated record storage devices (for example, magnetic discs and tapes) if associated computer...

19 CFR 181.12 - Maintenance and availability of records.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 19 Customs Duties 2 2010-04-01 2010-04-01 false Maintenance and availability of records. 181.12 Section 181.12 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY... or in automated record storage devices (for example, magnetic discs and tapes) if associated computer...

77 FR 44258 - Agency Information Collection Activities: Exportation of Used Self-Propelled Vehicles

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-27

... Activities: Exportation of Used Self-Propelled Vehicles AGENCY: U.S. Customs and Border Protection (CBP... information collection requirement concerning the Exportation of Used Self-Propelled Vehicles. This request... clarity of the information to be collected; (d) ways to minimize the burden including the use of automated...

Detection and monitoring of cardiotoxicity-what does modern cardiology offer?

PubMed

Jurcut, Ruxandra; Wildiers, Hans; Ganame, Javier; D'hooge, Jan; Paridaens, Robert; Voigt, Jens-Uwe

2008-05-01

With new anticancer therapies, many patients can have a long life expectancy. Treatment-related comorbidities become an issue for cancer survivors. Cardiac toxicity remains an important side effect of anticancer therapies. Myocardial dysfunction can become apparent early or long after end of therapy and may be irreversible. Detection of cardiac injury is crucial since it may facilitate early therapeutic measures. Traditionally, chemotherapy-induced cardiotoxicity has been detected by measuring changes in left ventricular ejection fraction. This parameter is, however, insensitive to subtle changes in myocardial function as they occur in early cardiotoxicity. This review will discuss conventional and modern cardiologic approaches of assessing myocardial function. It will focus on Doppler myocardial imaging, a method which allows to sensitively measure myocardial function parameters like myocardial velocity, deformation (strain), or deformation rate (strain rate) and which has been shown to reliably detect early abnormalities in both regional and global myocardial function in an early stage. Other newer echocardiographic function estimators are based on automated border detection algorithms and ultrasonic integrated backscatter analysis. A further technique to be discussed is dobutamine stress echocardiography. The use of new biomarkers like B-type natriuretic peptide and troponin and less often used imaging techniques like magnetic resonance imaging and computed tomography will also be mentioned.

Two critical periods in early visual cortex during figure-ground segregation.

PubMed

Wokke, Martijn E; Sligte, Ilja G; Steven Scholte, H; Lamme, Victor A F

2012-11-01

The ability to distinguish a figure from its background is crucial for visual perception. To date, it remains unresolved where and how in the visual system different stages of figure-ground segregation emerge. Neural correlates of figure border detection have consistently been found in early visual cortex (V1/V2). However, areas V1/V2 have also been frequently associated with later stages of figure-ground segregation (such as border ownership or surface segregation). To causally link activity in early visual cortex to different stages of figure-ground segregation, we briefly disrupted activity in areas V1/V2 at various moments in time using transcranial magnetic stimulation (TMS). Prior to stimulation we presented stimuli that made it possible to differentiate between figure border detection and surface segregation. We concurrently recorded electroencephalographic (EEG) signals to examine how neural correlates of figure-ground segregation were affected by TMS. Results show that disruption of V1/V2 in an early time window (96-119 msec) affected detection of figure stimuli and affected neural correlates of figure border detection, border ownership, and surface segregation. TMS applied in a relatively late time window (236-259 msec) selectively deteriorated performance associated with surface segregation. We conclude that areas V1/V2 are not only essential in an early stage of figure-ground segregation when figure borders are detected, but subsequently causally contribute to more sophisticated stages of figure-ground segregation such as surface segregation.

Two critical periods in early visual cortex during figure–ground segregation

PubMed Central

Wokke, Martijn E; Sligte, Ilja G; Steven Scholte, H; Lamme, Victor A F

2012-01-01

The ability to distinguish a figure from its background is crucial for visual perception. To date, it remains unresolved where and how in the visual system different stages of figure–ground segregation emerge. Neural correlates of figure border detection have consistently been found in early visual cortex (V1/V2). However, areas V1/V2 have also been frequently associated with later stages of figure–ground segregation (such as border ownership or surface segregation). To causally link activity in early visual cortex to different stages of figure–ground segregation, we briefly disrupted activity in areas V1/V2 at various moments in time using transcranial magnetic stimulation (TMS). Prior to stimulation we presented stimuli that made it possible to differentiate between figure border detection and surface segregation. We concurrently recorded electroencephalographic (EEG) signals to examine how neural correlates of figure–ground segregation were affected by TMS. Results show that disruption of V1/V2 in an early time window (96–119 msec) affected detection of figure stimuli and affected neural correlates of figure border detection, border ownership, and surface segregation. TMS applied in a relatively late time window (236–259 msec) selectively deteriorated performance associated with surface segregation. We conclude that areas V1/V2 are not only essential in an early stage of figure–ground segregation when figure borders are detected, but subsequently causally contribute to more sophisticated stages of figure–ground segregation such as surface segregation. PMID:23170239

Energy Assessment of Automated Mobility Districts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yuche

Automated vehicles (AVs) are increasingly being discussed as the basis for on-demand mobility services, introducing a new paradigm in which a fleet of AVs displace private automobiles for day-to-day travel in dense activity districts. This project examines such a concept to displace privately owned automobiles within a region containing dense activity generators (jobs, retail, entertainment, etc.), referred to as an automated mobility district (AMDs). The project reviews several such districts including airport, college campuses, business parks, downtown urban cores, and military bases, with examples of previous attempts to meet the mobility needs apart from private automobiles, some with automated technologymore » and others with more traditional transit based solutions. The issues and benefits of AMDs are framed within the perspective of intra-district, inter-district, and border issues, and the requirements for a modeling framework are identified to adequately reflect the breadth of mobility, energy, and emissions impact anticipated with AMDs.« less

On precise phase difference measurement approach using border stability of detection resolution.

PubMed

Bai, Lina; Su, Xin; Zhou, Wei; Ou, Xiaojuan

2015-01-01

For the precise phase difference measurement, this paper develops an improved dual phase coincidence detection method. The measurement resolution of the digital phase coincidence detection circuits is always limited, for example, only at the nanosecond level. This paper reveals a new way to improve the phase difference measurement precision by using the border stability of the circuit detection fuzzy areas. When a common oscillator signal is used to detect the phase coincidence with the two comparison signals, there will be two detection fuzzy areas for the reason of finite detection resolution surrounding the strict phase coincidence. Border stability of fuzzy areas and the fluctuation difference of the two fuzzy areas can be even finer than the picoseconds level. It is shown that the system resolution obtained only depends on the stability of the circuit measurement resolution which is much better than the measurement device resolution itself.

75 FR 19655 - Notice of Meeting of the Advisory Committee on Commercial Operations of Customs and Border...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-15

... Subcommittee. 5. Automation Subcommittee. 6. Import Safety. 7. Bond Subcommittee. 8. Trade Facilitation... Services for Individuals With Disabilities For information on facilities or services for individuals with disabilities or to request special assistance at the meeting, contact Ms. Wanda Tate as soon as possible. Dated...

77 FR 30297 - Privacy Act of 1974; U.S. Customs and Border Protection, DHS/CBP-006-Automated Targeting System...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-22

... Exams; for the combination of license plate, Department of Motor Vehicle (DMV) registration data and... combination of license plate, Department of Motor Vehicle (DMV) registration data and biographical data...; the combination of license plate, Department of Motor Vehicle (DMV) registration data and biographical...

E-commerce trade in invasive plants.

PubMed

Humair, Franziska; Humair, Luc; Kuhn, Fabian; Kueffer, Christoph

2015-12-01

Biological invasions are a major concern in conservation, especially because global transport of species is still increasing rapidly. Conservationists hope to anticipate and thus prevent future invasions by identifying and regulating potentially invasive species through species risk assessments and international trade regulations. Among many introduction pathways of non-native species, horticulture is a particularly important driver of plant invasions. In recent decades, the horticultural industry expanded globally and changed structurally through the emergence of new distribution channels, including internet trade (e-commerce). Using an automated search algorithm, we surveyed, on a daily basis, e-commerce trade on 10 major online auction sites (including eBay) of approximately three-fifths of the world's spermatophyte flora. Many recognized invasive plant species (>500 species) (i.e., species associated with ecological or socio-economic problems) were traded daily worldwide on the internet. A markedly higher proportion of invasive than non-invasive species were available online. Typically, for a particular plant family, 30-80% of recognized invasive species were detected on an auction site, but only a few percentages of all species in the plant family were detected on a site. Families that were more traded had a higher proportion of invasive species than families that were less traded. For woody species, there was a significant positive relationship between the number of regions where a species was sold and the number of regions where it was invasive. Our results indicate that biosecurity is not effectively regulating online plant trade. In the future, automated monitoring of e-commerce may help prevent the spread of invasive species, provide information on emerging trade connectivity across national borders, and be used in horizon scanning exercises for early detection of new species and their geographic source areas in international trade. © 2015 Society for Conservation Biology.

Comparison of algorithms for automatic border detection of melanoma in dermoscopy images

NASA Astrophysics Data System (ADS)

Srinivasa Raghavan, Sowmya; Kaur, Ravneet; LeAnder, Robert

2016-09-01

Melanoma is one of the most rapidly accelerating cancers in the world [1]. Early diagnosis is critical to an effective cure. We propose a new algorithm for more accurately detecting melanoma borders in dermoscopy images. Proper border detection requires eliminating occlusions like hair and bubbles by processing the original image. The preprocessing step involves transforming the RGB image to the CIE L*u*v* color space, in order to decouple brightness from color information, then increasing contrast, using contrast-limited adaptive histogram equalization (CLAHE), followed by artifacts removal using a Gaussian filter. After preprocessing, the Chen-Vese technique segments the preprocessed images to create a lesion mask which undergoes a morphological closing operation. Next, the largest central blob in the lesion is detected, after which, the blob is dilated to generate an image output mask. Finally, the automatically-generated mask is compared to the manual mask by calculating the XOR error [3]. Our border detection algorithm was developed using training and test sets of 30 and 20 images, respectively. This detection method was compared to the SRM method [4] by calculating the average XOR error for each of the two algorithms. Average error for test images was 0.10, using the new algorithm, and 0.99, using SRM method. In comparing the average error values produced by the two algorithms, it is evident that the average XOR error for our technique is lower than the SRM method, thereby implying that the new algorithm detects borders of melanomas more accurately than the SRM algorithm.

In search for a gold-standard procedure to count motor neurons in the spinal cord.

PubMed

Ferrucci, Michela; Lazzeri, Gloria; Flaibani, Marina; Biagioni, Francesca; Cantini, Federica; Madonna, Michele; Bucci, Domenico; Limanaqi, Fiona; Soldani, Paola; Fornai, Francesco

2018-03-14

Counting motor neurons within the spinal cord and brainstem represents a seminal step to comprehend the anatomy and physiology of the final common pathway sourcing from the CNS. Motor neuron loss allows to assess the severity of motor neuron disorders while providing a tool to assess disease modifying effects. Counting motor neurons at first implies gold standard identification methods. In fact, motor neurons may occur within mixed nuclei housing a considerable amount of neurons other than motor neurons. In the present review, we analyse various approaches to count motor neurons emphasizing both the benefits and bias of each protocol. A special emphasis is placed on discussing automated stereology. When automated stereology does not take into account site-specificity and does not distinguish between heterogeneous neuronal populations, it may confound data making such a procedure a sort of "guide for the perplex". Thus, if on the one hand automated stereology improves our ability to quantify neuronal populations, it may also hide false positives/negatives in neuronal counts. For instance, classic staining for antigens such as SMI-32, SMN and ChAT, which are routinely considered to be specific for motor neurons, may also occur in other neuronal types of the spinal cord. Even site specificity within Lamina IX may be misleading due to neuronal populations having a size and shape typical of motor neurons. This is the case of spinal border cells, which often surpass the border of Lamina VII and intermingle with motor neurons of Lamina IX. The present article discusses the need to join automated stereology with a dedicated knowledge of each specific neuroanatomical setting.

Radiation Detection at Borders for Homeland Security

NASA Astrophysics Data System (ADS)

Kouzes, Richard

2004-05-01

Countries around the world are deploying radiation detection instrumentation to interdict the illegal shipment of radioactive material crossing international borders at land, rail, air, and sea ports of entry. These efforts include deployments in the US and a number of European and Asian countries by governments and international agencies. Items of concern include radiation dispersal devices (RDD), nuclear warheads, and special nuclear material (SNM). Radiation portal monitors (RPMs) are used as the main screening tool for vehicles and cargo at borders, supplemented by handheld detectors, personal radiation detectors, and x-ray imaging systems. Some cargo contains naturally occurring radioactive material (NORM) that triggers "nuisance" alarms in RPMs at these border crossings. Individuals treated with medical radiopharmaceuticals also produce nuisance alarms and can produce cross-talk between adjacent lanes of a multi-lane deployment. The operational impact of nuisance alarms can be significant at border crossings. Methods have been developed for reducing this impact without negatively affecting the requirements for interdiction of radioactive materials of interest. Plastic scintillator material is commonly used in RPMs for the detection of gamma rays from radioactive material, primarily due to the efficiency per unit cost compared to other detection materials. The resolution and lack of full-energy peaks in the plastic scintillator material prohibits detailed spectroscopy. However, the limited spectroscopic information from plastic scintillator can be exploited to provide some discrimination. Energy-based algorithms used in RPMs can effectively exploit the crude energy information available from a plastic scintillator to distinguish some NORM. Whenever NORM cargo limits the level of the alarm threshold, energy-based algorithms produce significantly better detection probabilities for small SNM sources than gross-count algorithms. This presentation discusses experience with RPMs for interdiction of radioactive materials at borders.

Stop! border ahead: Automatic detection of subthalamic exit during deep brain stimulation surgery.

PubMed

Valsky, Dan; Marmor-Levin, Odeya; Deffains, Marc; Eitan, Renana; Blackwell, Kim T; Bergman, Hagai; Israel, Zvi

2017-01-01

Microelectrode recordings along preplanned trajectories are often used for accurate definition of the subthalamic nucleus (STN) borders during deep brain stimulation (DBS) surgery for Parkinson's disease. Usually, the demarcation of the STN borders is performed manually by a neurophysiologist. The exact detection of the borders is difficult, especially detecting the transition between the STN and the substantia nigra pars reticulata. Consequently, demarcation may be inaccurate, leading to suboptimal location of the DBS lead and inadequate clinical outcomes. We present machine-learning classification procedures that use microelectrode recording power spectra and allow for real-time, high-accuracy discrimination between the STN and substantia nigra pars reticulata. A support vector machine procedure was tested on microelectrode recordings from 58 trajectories that included both STN and substantia nigra pars reticulata that achieved a 97.6% consistency with human expert classification (evaluated by 10-fold cross-validation). We used the same data set as a training set to find the optimal parameters for a hidden Markov model using both microelectrode recording features and trajectory history to enable real-time classification of the ventral STN border (STN exit). Seventy-three additional trajectories were used to test the reliability of the learned statistical model in identifying the exit from the STN. The hidden Markov model procedure identified the STN exit with an error of 0.04 ± 0.18 mm and detection reliability (error < 1 mm) of 94%. The results indicate that robust, accurate, and automatic real-time electrophysiological detection of the ventral STN border is feasible. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.

Security Applications Of Computer Motion Detection

NASA Astrophysics Data System (ADS)

Bernat, Andrew P.; Nelan, Joseph; Riter, Stephen; Frankel, Harry

1987-05-01

An important area of application of computer vision is the detection of human motion in security systems. This paper describes the development of a computer vision system which can detect and track human movement across the international border between the United States and Mexico. Because of the wide range of environmental conditions, this application represents a stringent test of computer vision algorithms for motion detection and object identification. The desired output of this vision system is accurate, real-time locations for individual aliens and accurate statistical data as to the frequency of illegal border crossings. Because most detection and tracking routines assume rigid body motion, which is not characteristic of humans, new algorithms capable of reliable operation in our application are required. Furthermore, most current detection and tracking algorithms assume a uniform background against which motion is viewed - the urban environment along the US-Mexican border is anything but uniform. The system works in three stages: motion detection, object tracking and object identi-fication. We have implemented motion detection using simple frame differencing, maximum likelihood estimation, mean and median tests and are evaluating them for accuracy and computational efficiency. Due to the complex nature of the urban environment (background and foreground objects consisting of buildings, vegetation, vehicles, wind-blown debris, animals, etc.), motion detection alone is not sufficiently accurate. Object tracking and identification are handled by an expert system which takes shape, location and trajectory information as input and determines if the moving object is indeed representative of an illegal border crossing.

Initial Assessment and Modeling Framework Development for Automated Mobility Districts: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hou, Yi; Young, Stanley E; Garikapati, Venu

Automated vehicles (AVs) are increasingly being discussed as the basis for on-demand mobility services, introducing a new paradigm in which a fleet of AVs displaces private automobiles for day-to-day travel in dense activity districts. This paper examines a concept to displace privately owned automobiles within a region containing dense activity generators (jobs, retail, entertainment, etc.), referred to as an automated mobility district (AMD). This paper reviews several such districts, including airports, college campuses, business parks, downtown urban cores, and military bases, with examples of previous attempts to meet the mobility needs apart from private automobiles, some with automated technology andmore » others with more traditional transit-based solutions. The issues and benefits of AMDs are framed within the perspective of intra-district, inter-district, and border issues, and the requirements for a modeling framework are identified to adequately reflect the breadth of mobility, energy, and emissions impact anticipated with AMDs« less

Simultaneous extraction of centerlines, stenosis, and thrombus detection in renal CT angiography

NASA Astrophysics Data System (ADS)

Subramanyan, Krishna; Durgan, Jacob; Hodgkiss, Thomas D.; Chandra, Shalabh

2004-05-01

The Renal Artery Stenosis (RAS) is the major cause of renovascular hypertension and CT angiography has shown tremendous promise as a noninvasive method for reliably detecting renal artery stenosis. The purpose of this study was to validate the semi-automated methods to assist in extraction of renal branches and characterizing the associated renal artery stenosis. Automatically computed diagnostic images such as straight MIP, curved MPR, cross-sections, and diameters from multi-slice CT are presented and evaluated for its acceptance. We used vessel-tracking image processing methods to extract the aortic-renal vessel tree in a CT data in axial slice images. Next, from the topology and anatomy of the aortic vessel tree, the stenosis, and thrombus section and branching of the renal arteries are extracted. The results are presented in curved MPR and continuously variable MIP images. In this study, 15 patients were scanned with contrast on Mx8000 CT scanner (Philips Medical Systems), with 1.0 mm thickness, 0.5mm slice spacing, and 120kVp and a stack of 512x512x150 volume sets were reconstructed. The automated image processing took less than 50 seconds to compute the centerline and borders of the aortic/renal vessel tree. The overall assessment of manual and automatically generated stenosis yielded a weighted kappa statistic of 0.97 at right renal arteries, 0.94 at the left renal branches. The thrombus region contoured manually and semi-automatically agreed upon at 0.93. The manual time to process each case is approximately 25 to 30 minutes.

19 CFR 4.76 - Procedures and responsibilities of carriers filing outbound vessel manifest information via the AES.

Code of Federal Regulations, 2012 CFR

2012-04-01

... outbound vessel manifest information via the AES. 4.76 Section 4.76 Customs Duties U.S. CUSTOMS AND BORDER... manifest information via the AES. (a) The sea carrier's module. The Sea Carrier's Module is a component of the Automated Export System (AES) (see, part 192, subpart B, of this chapter) that allows for the...

19 CFR 4.76 - Procedures and responsibilities of carriers filing outbound vessel manifest information via the AES.

Code of Federal Regulations, 2014 CFR

2014-04-01

... outbound vessel manifest information via the AES. 4.76 Section 4.76 Customs Duties U.S. CUSTOMS AND BORDER... manifest information via the AES. (a) The sea carrier's module. The Sea Carrier's Module is a component of the Automated Export System (AES) (see, part 192, subpart B, of this chapter) that allows for the...

19 CFR 4.76 - Procedures and responsibilities of carriers filing outbound vessel manifest information via the AES.

Code of Federal Regulations, 2011 CFR

2011-04-01

... outbound vessel manifest information via the AES. 4.76 Section 4.76 Customs Duties U.S. CUSTOMS AND BORDER... manifest information via the AES. (a) The sea carrier's module. The Sea Carrier's Module is a component of the Automated Export System (AES) (see, part 192, subpart B, of this chapter) that allows for the...

19 CFR 4.76 - Procedures and responsibilities of carriers filing outbound vessel manifest information via the AES.

Code of Federal Regulations, 2013 CFR

2013-04-01

... outbound vessel manifest information via the AES. 4.76 Section 4.76 Customs Duties U.S. CUSTOMS AND BORDER... manifest information via the AES. (a) The sea carrier's module. The Sea Carrier's Module is a component of the Automated Export System (AES) (see, part 192, subpart B, of this chapter) that allows for the...

19 CFR 4.76 - Procedures and responsibilities of carriers filing outbound vessel manifest information via the AES.

Code of Federal Regulations, 2010 CFR

2010-04-01

... outbound vessel manifest information via the AES. 4.76 Section 4.76 Customs Duties U.S. CUSTOMS AND BORDER... manifest information via the AES. (a) The sea carrier's module. The Sea Carrier's Module is a component of the Automated Export System (AES) (see, part 192, subpart B, of this chapter) that allows for the...

Changes in intestinal absorption of nutrients and brush border glycoproteins after total parenteral nutrition in rats.

PubMed Central

Miura, S; Tanaka, S; Yoshioka, M; Serizawa, H; Tashiro, H; Shiozaki, H; Imaeda, H; Tsuchiya, M

1992-01-01

The effect of total parenteral nutrition on nutrients absorption and glycoprotein changes of brush border membrane was examined in rat small intestine. In total parenteral nutrition rats, a marked decrease in activity of brush border enzymes was observed mainly in the proximal and middle segments of the intestine. Galactose perfusion of jejunal segment showed that hexose absorption was significantly inhibited, while intestinal absorption of glycine or dipeptide, glycylglycine was not significantly affected by total parenteral nutrition treatment. When brush border membrane glycoprotein profile was examined by [3H]-glucosamine or [3H]-fucose incorporation into jejunal loops, significant changes were observed in the glycoprotein pattern of brush border membrane especially in the high molecular weight range over 120 kDa after total parenteral nutrition treatment, suggesting strong dependency of glycoprotein synthesis on luminal substances. Molecular weight of sucrase isomaltase in brush border membrane detected by specific antibody showed no significant difference, however, in total parenteral nutrition and control rats. Also, molecular weight of specific sodium glucose cotransporter of intestinal brush border membrane detected by selective photoaffinity labelling was not altered in total parenteral nutrition rats. It may be that prolonged absence of oral food intake may produce significant biochemical changes in brush border membrane glycoprotein and absorptive capacity of small intestine, but these changes were not observed in all brush border membrane glycoproteins. Images Figure 1 Figure 2 Figure 3 Figure 4 PMID:1582592

Transitioning to future air traffic management: effects of imperfect automation on controller attention and performance.

PubMed

Rovira, Ericka; Parasuraman, Raja

2010-06-01

This study examined whether benefits of conflict probe automation would occur in a future air traffic scenario in which air traffic service providers (ATSPs) are not directly responsible for freely maneuvering aircraft but are controlling other nonequipped aircraft (mixed-equipage environment). The objective was to examine how the type of automation imperfection (miss vs. false alarm) affects ATSP performance and attention allocation. Research has shown that the type of automation imperfection leads to differential human performance costs. Participating in four 30-min scenarios were 12 full-performance-level ATSPs. Dependent variables included conflict detection and resolution performance, eye movements, and subjective ratings of trust and self confidence. ATSPs detected conflicts faster and more accurately with reliable automation, as compared with manual performance. When the conflict probe automation was unreliable, conflict detection performance declined with both miss (25% conflicts detected) and false alarm automation (50% conflicts detected). When the primary task of conflict detection was automated, even highly reliable yet imperfect automation (miss or false alarm) resulted in serious negative effects on operator performance. The further in advance that conflict probe automation predicts a conflict, the greater the uncertainty of prediction; thus, designers should provide users with feedback on the state of the automation or other tools that allow for inspection and analysis of the data underlying the conflict probe algorithm.

An Automated Energy Detection Algorithm Based on Morphological Filter Processing with a Modified Watershed Transform

DTIC Science & Technology

2018-01-01

ARL-TR-8270 ● JAN 2018 US Army Research Laboratory An Automated Energy Detection Algorithm Based on Morphological Filter...Automated Energy Detection Algorithm Based on Morphological Filter Processing with a Modified Watershed Transform by Kwok F Tom Sensors and Electron...1 October 2016–30 September 2017 4. TITLE AND SUBTITLE An Automated Energy Detection Algorithm Based on Morphological Filter Processing with a

An Artificial Intelligence Approach to Automatic Left Ventricular Border Detection in 2-D Echocardiography

PubMed Central

Buchan, Iris; Covvey, H. Dominic; Rakowski, Harry

1985-01-01

A program has been developed for left ventricular (LV) border tracking on ultrasound images. For each frame, forty border points at equally-spaced angles around the LV center are found gradually during three passes. Pass 1 uses adaptive thresholding to find the most obvious border points. Pass 2 then uses an artificial intelligence technique of finding possible border path segments, associating a score with each, and, from paths with superior scores, obtaining more of the border points. Pass 3 closes any remaining gaps by interpolation. The program tracks the LV border quite well in spite of dropout and interference from intracardiac structures, except during end-systole. Multi-level passes provide a very useful structure for border tracking, with increasingly slow but more sophisticated algorithms possible at higher levels for use when earlier passes recognise failure.

The role of haemorrhage and exudate detection in automated grading of diabetic retinopathy.

PubMed

Fleming, Alan D; Goatman, Keith A; Philip, Sam; Williams, Graeme J; Prescott, Gordon J; Scotland, Graham S; McNamee, Paul; Leese, Graham P; Wykes, William N; Sharp, Peter F; Olson, John A

2010-06-01

Automated grading has the potential to improve the efficiency of diabetic retinopathy screening services. While disease/no disease grading can be performed using only microaneurysm detection and image-quality assessment, automated recognition of other types of lesions may be advantageous. This study investigated whether inclusion of automated recognition of exudates and haemorrhages improves the detection of observable/referable diabetic retinopathy. Images from 1253 patients with observable/referable retinopathy and 6333 patients with non-referable retinopathy were obtained from three grading centres. All images were reference-graded, and automated disease/no disease assessments were made based on microaneurysm detection and combined microaneurysm, exudate and haemorrhage detection. Introduction of algorithms for exudates and haemorrhages resulted in a statistically significant increase in the sensitivity for detection of observable/referable retinopathy from 94.9% (95% CI 93.5 to 96.0) to 96.6% (95.4 to 97.4) without affecting manual grading workload. Automated detection of exudates and haemorrhages improved the detection of observable/referable retinopathy.

Forest land cover change (1975-2000) in the Greater Border Lakes region

Treesearch

Peter T. Wolter; Brian R. Sturtevant; Brian R. Miranda; Sue M. Lietz; Phillip A. Townsend; John Pastor

2012-01-01

This document and accompanying maps describe land cover classifications and change detection for a 13.8 million ha landscape straddling the border between Minnesota, and Ontario, Canada (greater Border Lakes Region). Land cover classifications focus on discerning Anderson Level II forest and nonforest cover to track spatiotemporal changes in forest cover. Multi-...

Generating Impact Maps from Automatically Detected Bomb Craters in Aerial Wartime Images Using Marked Point Processes

NASA Astrophysics Data System (ADS)

Kruse, Christian; Rottensteiner, Franz; Hoberg, Thorsten; Ziems, Marcel; Rebke, Julia; Heipke, Christian

2018-04-01

The aftermath of wartime attacks is often felt long after the war ended, as numerous unexploded bombs may still exist in the ground. Typically, such areas are documented in so-called impact maps which are based on the detection of bomb craters. This paper proposes a method for the automatic detection of bomb craters in aerial wartime images that were taken during the Second World War. The object model for the bomb craters is represented by ellipses. A probabilistic approach based on marked point processes determines the most likely configuration of objects within the scene. Adding and removing new objects to and from the current configuration, respectively, changing their positions and modifying the ellipse parameters randomly creates new object configurations. Each configuration is evaluated using an energy function. High gradient magnitudes along the border of the ellipse are favored and overlapping ellipses are penalized. Reversible Jump Markov Chain Monte Carlo sampling in combination with simulated annealing provides the global energy optimum, which describes the conformance with a predefined model. For generating the impact map a probability map is defined which is created from the automatic detections via kernel density estimation. By setting a threshold, areas around the detections are classified as contaminated or uncontaminated sites, respectively. Our results show the general potential of the method for the automatic detection of bomb craters and its automated generation of an impact map in a heterogeneous image stock.

Automation in airport security X-ray screening of cabin baggage: Examining benefits and possible implementations of automated explosives detection.

PubMed

Hättenschwiler, Nicole; Sterchi, Yanik; Mendes, Marcia; Schwaninger, Adrian

2018-10-01

Bomb attacks on civil aviation make detecting improvised explosive devices and explosive material in passenger baggage a major concern. In the last few years, explosive detection systems for cabin baggage screening (EDSCB) have become available. Although used by a number of airports, most countries have not yet implemented these systems on a wide scale. We investigated the benefits of EDSCB with two different levels of automation currently being discussed by regulators and airport operators: automation as a diagnostic aid with an on-screen alarm resolution by the airport security officer (screener) or EDSCB with an automated decision by the machine. The two experiments reported here tested and compared both scenarios and a condition without automation as baseline. Participants were screeners at two international airports who differed in both years of work experience and familiarity with automation aids. Results showed that experienced screeners were good at detecting improvised explosive devices even without EDSCB. EDSCB increased only their detection of bare explosives. In contrast, screeners with less experience (tenure < 1 year) benefitted substantially from EDSCB in detecting both improvised explosive devices and bare explosives. A comparison of all three conditions showed that automated decision provided better human-machine detection performance than on-screen alarm resolution and no automation. This came at the cost of slightly higher false alarm rates on the human-machine system level, which would still be acceptable from an operational point of view. Results indicate that a wide-scale implementation of EDSCB would increase the detection of explosives in passenger bags and automated decision instead of automation as diagnostic aid with on screen alarm resolution should be considered. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Fast-time Simulation of an Automated Conflict Detection and Resolution Concept

NASA Technical Reports Server (NTRS)

Windhorst, Robert; Erzberger, Heinz

2006-01-01

This paper investigates the effect on the National Airspace System of reducing air traffc controller workload by automating conflict detection and resolution. The Airspace Concept Evaluation System is used to perform simulations of the Cleveland Center with conventional and with automated conflict detection and resolution concepts. Results show that the automated conflict detection and resolution concept significantly decreases growth of delay as traffic demand is increased in en-route airspace.

Integrating LPR with CCTV systems: problems and solutions

NASA Astrophysics Data System (ADS)

Bissessar, David; Gorodnichy, Dmitry O.

2011-06-01

A new generation of high-resolution surveillance cameras makes it possible to apply video processing and recognition techniques on live video feeds for the purpose of automatically detecting and identifying objects and events of interest. This paper addresses a particular application of detecting and identifying vehicles passing through a checkpoint. This application is of interest to border services agencies and is also related to many other applications. With many commercial automated License Plate Recognition (LPR) systems available on the market, some of which are available as a plug-in for surveillance systems, this application still poses many unresolved technological challenges, the main two of which are: i) multiple and often noisy license plate readings generated for the same vehicle, and ii) failure to detect a vehicle or license plate altogether when the license plate is occluded or not visible. This paper presents a solution to both of these problems. A data fusion technique based on the Levenshtein distance is used to resolve the first problem. An integration of a commercial LPR system with the in-house built Video Analytic Platform is used to solve the latter. The developed solution has been tested in field environments and has been shown to yield a substantial improvement over standard off-the-shelf LPR systems.

Terrain Commander: a next-generation remote surveillance system

NASA Astrophysics Data System (ADS)

Finneral, Henry J.

2003-09-01

Terrain Commander is a fully automated forward observation post that provides the most advanced capability in surveillance and remote situational awareness. The Terrain Commander system was selected by the Australian Government for its NINOX Phase IIB Unattended Ground Sensor Program with the first systems delivered in August of 2002. Terrain Commander offers next generation target detection using multi-spectral peripheral sensors coupled with autonomous day/night image capture and processing. Subsequent intelligence is sent back through satellite communications with unlimited range to a highly sophisticated central monitoring station. The system can "stakeout" remote locations clandestinely for 24 hours a day for months at a time. With its fully integrated SATCOM system, almost any site in the world can be monitored from virtually any other location in the world. Terrain Commander automatically detects and discriminates intruders by precisely cueing its advanced EO subsystem. The system provides target detection capabilities with minimal nuisance alarms combined with the positive visual identification that authorities demand before committing a response. Terrain Commander uses an advanced beamforming acoustic sensor and a distributed array of seismic, magnetic and passive infrared sensors to detect, capture images and accurately track vehicles and personnel. Terrain Commander has a number of emerging military and non-military applications including border control, physical security, homeland defense, force protection and intelligence gathering. This paper reviews the development, capabilities and mission applications of the Terrain Commander system.

Altered fingerprints: analysis and detection.

PubMed

Yoon, Soweon; Feng, Jianjiang; Jain, Anil K

2012-03-01

The widespread deployment of Automated Fingerprint Identification Systems (AFIS) in law enforcement and border control applications has heightened the need for ensuring that these systems are not compromised. While several issues related to fingerprint system security have been investigated, including the use of fake fingerprints for masquerading identity, the problem of fingerprint alteration or obfuscation has received very little attention. Fingerprint obfuscation refers to the deliberate alteration of the fingerprint pattern by an individual for the purpose of masking his identity. Several cases of fingerprint obfuscation have been reported in the press. Fingerprint image quality assessment software (e.g., NFIQ) cannot always detect altered fingerprints since the implicit image quality due to alteration may not change significantly. The main contributions of this paper are: 1) compiling case studies of incidents where individuals were found to have altered their fingerprints for circumventing AFIS, 2) investigating the impact of fingerprint alteration on the accuracy of a commercial fingerprint matcher, 3) classifying the alterations into three major categories and suggesting possible countermeasures, 4) developing a technique to automatically detect altered fingerprints based on analyzing orientation field and minutiae distribution, and 5) evaluating the proposed technique and the NFIQ algorithm on a large database of altered fingerprints provided by a law enforcement agency. Experimental results show the feasibility of the proposed approach in detecting altered fingerprints and highlight the need to further pursue this problem.

Evaluation of vincristine-associated myelosuppression in Border Collies.

PubMed

Lind, Denise L; Fidel, Janean L; Gay, John M; Mealey, Katrina L

2013-02-01

To determine whether Border Collies (ATP binding cassette subfamily B1 gene [ABCB1] wildtype) were more likely than other breeds to develop vincristine-associated myelosuppression (VAM) and, if so, whether this was caused by a mutation in ABCB1 distinct from ABCB1-1Δ. Phase 1 comprised 36 dogs with the ABCB1 wildtype, including 26 dogs with lymphoma (5 Border Collies and 21 dogs representing 13 other breeds) treated with vincristine in a previous study; phase 2 comprised 10 additional Border Collies, including 3 that developed VAM and 7 with an unknown phenotype. For phase 1, the prevalence of VAM in ABCB1-wildtype Border Collies was compared with that for ABCB1-wildtype dogs of other breeds with data from a previous study. For phase 2, additional Border Collies were included. Hematologic adverse reactions were graded with Veterinary Co-operative Oncology Group criteria. Genomic DNA was used to amplify and sequence all 27 exons of the canine ABCB1. Sequences from affected dogs were compared with those of unaffected dogs and dogs of unknown phenotype. 3 of 5 Border Collies with the ABCB1 wildtype developed VAM; this was significantly higher than the proportion of other dogs that developed VAM (0/21). A causative mutation for VAM in Border Collies was not identified, although 8 single nucleotide polymorphisms in ABCB1 were detected. Breed-associated sensitivity to vincristine unrelated to ABCB1 was detected in Border Collies. Veterinarians should be aware of this breed predisposition to VAM. Causes for this apparent breed-associated sensitivity should be explored.

Guiding automated left ventricular chamber segmentation in cardiac imaging using the concept of conserved myocardial volume.

PubMed

Garson, Christopher D; Li, Bing; Acton, Scott T; Hossack, John A

2008-06-01

The active surface technique using gradient vector flow allows semi-automated segmentation of ventricular borders. The accuracy of the algorithm depends on the optimal selection of several key parameters. We investigated the use of conservation of myocardial volume for quantitative assessment of each of these parameters using synthetic and in vivo data. We predicted that for a given set of model parameters, strong conservation of volume would correlate with accurate segmentation. The metric was most useful when applied to the gradient vector field weighting and temporal step-size parameters, but less effective in guiding an optimal choice of the active surface tension and rigidity parameters.

Automated Detection of Sepsis Using Electronic Medical Record Data: A Systematic Review.

PubMed

Despins, Laurel A

Severe sepsis and septic shock are global issues with high mortality rates. Early recognition and intervention are essential to optimize patient outcomes. Automated detection using electronic medical record (EMR) data can assist this process. This review describes automated sepsis detection using EMR data. PubMed retrieved publications between January 1, 2005 and January 31, 2015. Thirteen studies met study criteria: described an automated detection approach with the potential to detect sepsis or sepsis-related deterioration in real or near-real time; focused on emergency department and hospitalized neonatal, pediatric, or adult patients; and provided performance measures or results indicating the impact of automated sepsis detection. Detection algorithms incorporated systemic inflammatory response and organ dysfunction criteria. Systems in nine studies generated study or care team alerts. Care team alerts did not consistently lead to earlier interventions. Earlier interventions did not consistently translate to improved patient outcomes. Performance measures were inconsistent. Automated sepsis detection is potentially a means to enable early sepsis-related therapy but current performance variability highlights the need for further research.

Bridging the gap: from biometrics to forensics.

PubMed

Jain, Anil K; Ross, Arun

2015-08-05

Biometric recognition, or simply biometrics, refers to automated recognition of individuals based on their behavioural and biological characteristics. The success of fingerprints in forensic science and law enforcement applications, coupled with growing concerns related to border control, financial fraud and cyber security, has generated a huge interest in using fingerprints, as well as other biological traits, for automated person recognition. It is, therefore, not surprising to see biometrics permeating various segments of our society. Applications include smartphone security, mobile payment, border crossing, national civil registry and access to restricted facilities. Despite these successful deployments in various fields, there are several existing challenges and new opportunities for person recognition using biometrics. In particular, when biometric data is acquired in an unconstrained environment or if the subject is uncooperative, the quality of the ensuing biometric data may not be amenable for automated person recognition. This is particularly true in crime-scene investigations, where the biological evidence gleaned from a scene may be of poor quality. In this article, we first discuss how biometrics evolved from forensic science and how its focus is shifting back to its origin in order to address some challenging problems. Next, we enumerate the similarities and differences between biometrics and forensics. We then present some applications where the principles of biometrics are being successfully leveraged into forensics in order to solve critical problems in the law enforcement domain. Finally, we discuss new collaborative opportunities for researchers in biometrics and forensics, in order to address hitherto unsolved problems that can benefit society at large. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Bridging the gap: from biometrics to forensics

PubMed Central

Jain, Anil K.; Ross, Arun

2015-01-01

Biometric recognition, or simply biometrics, refers to automated recognition of individuals based on their behavioural and biological characteristics. The success of fingerprints in forensic science and law enforcement applications, coupled with growing concerns related to border control, financial fraud and cyber security, has generated a huge interest in using fingerprints, as well as other biological traits, for automated person recognition. It is, therefore, not surprising to see biometrics permeating various segments of our society. Applications include smartphone security, mobile payment, border crossing, national civil registry and access to restricted facilities. Despite these successful deployments in various fields, there are several existing challenges and new opportunities for person recognition using biometrics. In particular, when biometric data is acquired in an unconstrained environment or if the subject is uncooperative, the quality of the ensuing biometric data may not be amenable for automated person recognition. This is particularly true in crime-scene investigations, where the biological evidence gleaned from a scene may be of poor quality. In this article, we first discuss how biometrics evolved from forensic science and how its focus is shifting back to its origin in order to address some challenging problems. Next, we enumerate the similarities and differences between biometrics and forensics. We then present some applications where the principles of biometrics are being successfully leveraged into forensics in order to solve critical problems in the law enforcement domain. Finally, we discuss new collaborative opportunities for researchers in biometrics and forensics, in order to address hitherto unsolved problems that can benefit society at large. PMID:26101280

Automated detection of fundus photographic red lesions in diabetic retinopathy.

PubMed

Larsen, Michael; Godt, Jannik; Larsen, Nicolai; Lund-Andersen, Henrik; Sjølie, Anne Katrin; Agardh, Elisabet; Kalm, Helle; Grunkin, Michael; Owens, David R

2003-02-01

To compare a fundus image-analysis algorithm for automated detection of hemorrhages and microaneurysms with visual detection of retinopathy in patients with diabetes. Four hundred fundus photographs (35-mm color transparencies) were obtained in 200 eyes of 100 patients with diabetes who were randomly selected from the Welsh Community Diabetic Retinopathy Study. A gold standard reference was defined by classifying each patient as having or not having diabetic retinopathy based on overall visual grading of the digitized transparencies. A single-lesion visual grading was made independently, comprising meticulous outlining of all single lesions in all photographs and used to develop the automated red lesion detection system. A comparison of visual and automated single-lesion detection in replicating the overall visual grading was then performed. Automated red lesion detection demonstrated a specificity of 71.4% and a resulting sensitivity of 96.7% in detecting diabetic retinopathy when applied at a tentative threshold setting for use in diabetic retinopathy screening. The accuracy of 79% could be raised to 85% by adjustment of a single user-supplied parameter determining the balance between the screening priorities, for which a considerable range of options was demonstrated by the receiver-operating characteristic (area under the curve 90.3%). The agreement of automated lesion detection with overall visual grading (0.659) was comparable to the mean agreement of six ophthalmologists (0.648). Detection of diabetic retinopathy by automated detection of single fundus lesions can be achieved with a performance comparable to that of experienced ophthalmologists. The results warrant further investigation of automated fundus image analysis as a tool for diabetic retinopathy screening.

An Automated Energy Detection Algorithm Based on Morphological and Statistical Processing Techniques

DTIC Science & Technology

2018-01-09

ARL-TR-8272 ● JAN 2018 US Army Research Laboratory An Automated Energy Detection Algorithm Based on Morphological and...is no longer needed. Do not return it to the originator. ARL-TR-8272 ● JAN 2018 US Army Research Laboratory An Automated Energy ...4. TITLE AND SUBTITLE An Automated Energy Detection Algorithm Based on Morphological and Statistical Processing Techniques 5a. CONTRACT NUMBER

Left ventricular volume estimation in cardiac three-dimensional ultrasound: a semiautomatic border detection approach.

PubMed

van Stralen, Marijn; Bosch, Johan G; Voormolen, Marco M; van Burken, Gerard; Krenning, Boudewijn J; van Geuns, Robert-Jan M; Lancée, Charles T; de Jong, Nico; Reiber, Johan H C

2005-10-01

We propose a semiautomatic endocardial border detection method for three-dimensional (3D) time series of cardiac ultrasound (US) data based on pattern matching and dynamic programming, operating on two-dimensional (2D) slices of the 3D plus time data, for the estimation of full cycle left ventricular volume, with minimal user interaction. The presented method is generally applicable to 3D US data and evaluated on data acquired with the Fast Rotating Ultrasound (FRU-) Transducer, developed by Erasmus Medical Center (Rotterdam, the Netherlands), a conventional phased-array transducer, rotating at very high speed around its image axis. The detection is based on endocardial edge pattern matching using dynamic programming, which is constrained by a 3D plus time shape model. It is applied to an automatically selected subset of 2D images of the original data set, for typically 10 equidistant rotation angles and 16 cardiac phases (160 images). Initialization requires the drawing of four contours per patient manually. We evaluated this method on 14 patients against MRI end-diastole and end-systole volumes. Initialization requires the drawing of four contours per patient manually. We evaluated this method on 14 patients against MRI end-diastolic (ED) and end-systolic (ES) volumes. The semiautomatic border detection approach shows good correlations with MRI ED/ES volumes (r = 0.938) and low interobserver variability (y = 1.005x - 16.7, r = 0.943) over full-cycle volume estimations. It shows a high consistency in tracking the user-defined initial borders over space and time. We show that the ease of the acquisition using the FRU-transducer and the semiautomatic endocardial border detection method together can provide a way to quickly estimate the left ventricular volume over the full cardiac cycle using little user interaction.

Microsensors for border patrol applications

NASA Astrophysics Data System (ADS)

Falkofske, Dwight; Krantz, Brian; Shimazu, Ron; Berglund, Victor

2005-05-01

A top concern in homeland security efforts is the lack of ability to monitor the thousands of miles of open border with our neighbors. It is not currently feasible to continually monitor the borders for illegal intrusions. The MicroSensor System (MSS) seeks to achieve a low-cost monitoring solution that can be efficiently deployed for border patrol applications. The modifications and issues regarding the unique requirements of this application will be discussed and presented. The MicroSensor System was developed by the Defense Microelectronics Activity (DMEA) for military applications, but border patrol applications, with their unique sensor requirements, demand careful adaptation and modification from the military application. Adaptation of the existing sensor design for border applications has been initiated. Coverage issues, communications needs, and other requirements need to be explored for the border patrol application. Currently, border patrol has a number of deficiencies that can be addressed with a microsensor network. First, a distributed networked sensor field could mitigate the porous border intruder detection problem. Second, a unified database needs to be available to identify aliens attempting to cross into the United States. This database needs to take unique characteristics (e.g. biometrics, fingerprints) recovered from a specialized field unit to reliably identify intruders. Finally, this sensor network needs to provide a communication ability to allow border patrol officers to have quick access to intrusion information as well as equipment tracking and voice communication. MSS already addresses the sensing portion of the solution, including detection of acoustic, infrared, magnetic, and seismic events. MSS also includes a low-power networking protocol to lengthen the battery life. In addition to current military requirements, MSS needs a solar panel solution to extend its battery life to 5 years, and an additional backbone communication link. Expanding the capabilities of MSS will go a long way to improving the security of the nation's porous borders.

Interactive tele-radiological segmentation systems for treatment and diagnosis.

PubMed

Zimeras, S; Gortzis, L G

2012-01-01

Telehealth is the exchange of health information and the provision of health care services through electronic information and communications technology, where participants are separated by geographic, time, social and cultural barriers. The shift of telemedicine from desktop platforms to wireless and mobile technologies is likely to have a significant impact on healthcare in the future. It is therefore crucial to develop a general information exchange e-medical system to enables its users to perform online and offline medical consultations through diagnosis. During the medical diagnosis, image analysis techniques combined with doctor's opinions could be useful for final medical decisions. Quantitative analysis of digital images requires detection and segmentation of the borders of the object of interest. In medical images, segmentation has traditionally been done by human experts. Even with the aid of image processing software (computer-assisted segmentation tools), manual segmentation of 2D and 3D CT images is tedious, time-consuming, and thus impractical, especially in cases where a large number of objects must be specified. Substantial computational and storage requirements become especially acute when object orientation and scale have to be considered. Therefore automated or semi-automated segmentation techniques are essential if these software applications are ever to gain widespread clinical use. The main purpose of this work is to analyze segmentation techniques for the definition of anatomical structures under telemedical systems.

An ultra-bright white LED based non-contact skin cancer imaging system with polarization control

NASA Astrophysics Data System (ADS)

Günther, A.; Basu, C.; Roth, B.; Meinhardt-Wollweber, M.

2013-06-01

Early detection and excision of melanoma skin cancer is crucial for a successful therapy. Dermoscopy in direct contact with the skin is routinely used for inspection, but screening is time consuming for high-risk patients with a large number of nevi. Features like symmetry, border, color and most importantly changes like growth or depigmentation of a nevus may indicate malignancy. We present a non-contact remote imaging system for human melanocytic nevi with homogenous illumination by an ultra-bright white LED. The advantage compared to established dermoscopy systems requiring direct skin contact is that deformation of raised nevi is avoided and full-body scans of the patients may time-efficiently be obtained while they are in a lying, comfortable position. This will ultimately allow for automated screening in the future. In addition, calibration of true color rendering, which is essential for distinguishing between benign and malignant lesions and to ensure reproducibility and comparison between individual check-ups in order to follow nevi evolution is implemented as well as suppression of specular highlights on the skin surface by integration of polarizing filters. Important features of the system which will be crucial for future integration into automated systems are the possibility to record images without artifacts in combination with short exposure times which both reduce image blurring caused by patient motion.

Driver Vigilance in Automated Vehicles: Hazard Detection Failures Are a Matter of Time.

PubMed

Greenlee, Eric T; DeLucia, Patricia R; Newton, David C

2018-06-01

The primary aim of the current study was to determine whether monitoring the roadway for hazards during automated driving results in a vigilance decrement. Although automated vehicles are relatively novel, the nature of human-automation interaction within them has the classic hallmarks of a vigilance task. Drivers must maintain attention for prolonged periods of time to detect and respond to rare and unpredictable events, for example, roadway hazards that automation may be ill equipped to detect. Given the similarity with traditional vigilance tasks, we predicted that drivers of a simulated automated vehicle would demonstrate a vigilance decrement in hazard detection performance. Participants "drove" a simulated automated vehicle for 40 minutes. During that time, their task was to monitor the roadway for roadway hazards. As predicted, hazard detection rate declined precipitously, and reaction times slowed as the drive progressed. Further, subjective ratings of workload and task-related stress indicated that sustained monitoring is demanding and distressing and it is a challenge to maintain task engagement. Monitoring the roadway for potential hazards during automated driving results in workload, stress, and performance decrements similar to those observed in traditional vigilance tasks. To the degree that vigilance is required of automated vehicle drivers, performance errors and associated safety risks are likely to occur as a function of time on task. Vigilance should be a focal safety concern in the development of vehicle automation.

Development of automated endoscopes for dimensional micro-measurements

NASA Astrophysics Data System (ADS)

Hrebabetzky, Frank

2013-04-01

Increasing demands for product quality and outsourcing of production in the automobile industry lead to in­ creasingly tight tolerances for the components. In the area of metal-mechanics these are largely dimensional and require frequently uncertainties in the micron region. For optical instruments this means microscopical resolu­ tion. Dimensional measurement with uncertainties of some microns is nothing new, state of the art equipment in fact goes far below. The task becomes difficult if the measurements have to be carried out in an industrial production environment - and deep inside a bore hole. This paper describes the development of an automatic measurement system for internal dimensions of brake master cylinders, specifically the development of endoscopes, illuminations for edge detection, and integration with other sensors, actuators and controllers. The most demanding part was the endoscope development, because, surprisingly, no commercial product for microscopic view and precision measurements was found on the market. As the market for such measurement machines is very small, and as the requirements were different for each endoscope, the budget allowed only the development of prototypes, using readily available optical components. Borders between faces with different orientation of metallic structures can be difficult do detect. A satisfactory metrological performance can be achieved only with carefully shaped illumination, even if the source is a simple LED (light emitting diode). The automation was responsible for the largest part of the overall cost, coming from the desire for a high throughput of the measurement machine, even when operated by not highly qualified personnel. With the safety requirements satisfied, such a device ends up as a pretty complex equipment. Nevertheless, these aspects will be mentioned only for completeness, because standard components and methods were applied.

SNM-DAT: Simulation of a heterogeneous network for nuclear border security

NASA Astrophysics Data System (ADS)

Nemzek, R.; Kenyon, G.; Koehler, A.; Lee, D. M.; Priedhorsky, W.; Raby, E. Y.

2007-08-01

We approach the problem of detecting Special Nuclear Material (SNM) smuggling across open borders by modeling a heterogeneous sensor network using an agent-based simulation. Our simulation SNM Data Analysis Tool (SNM-DAT) combines fixed seismic, metal, and radiation detectors with a mobile gamma spectrometer. Decision making within the simulation determines threat levels by combined signatures. The spectrometer is a limited-availability asset, and is only deployed for substantial threats. "Crossers" can be benign or carrying shielded SNM. Signatures and sensors are physics based, allowing us to model realistic sensor networks. The heterogeneous network provides great gains in detection efficiency compared to a radiation-only system. We can improve the simulation through better sensor and terrain models, additional signatures, and crossers that mimic actual trans-border traffic. We expect further gains in our ability to design sensor networks as we learn the emergent properties of heterogeneous detection, and potential adversary responses.

Full-text automated detection of surgical site infections secondary to neurosurgery in Rennes, France.

PubMed

Campillo-Gimenez, Boris; Garcelon, Nicolas; Jarno, Pascal; Chapplain, Jean Marc; Cuggia, Marc

2013-01-01

The surveillance of Surgical Site Infections (SSI) contributes to the management of risk in French hospitals. Manual identification of infections is costly, time-consuming and limits the promotion of preventive procedures by the dedicated teams. The introduction of alternative methods using automated detection strategies is promising to improve this surveillance. The present study describes an automated detection strategy for SSI in neurosurgery, based on textual analysis of medical reports stored in a clinical data warehouse. The method consists firstly, of enrichment and concept extraction from full-text reports using NOMINDEX, and secondly, text similarity measurement using a vector space model. The text detection was compared to the conventional strategy based on self-declaration and to the automated detection using the diagnosis-related group database. The text-mining approach showed the best detection accuracy, with recall and precision equal to 92% and 40% respectively, and confirmed the interest of reusing full-text medical reports to perform automated detection of SSI.

Experience of automation failures in training: effects on trust, automation bias, complacency and performance.

PubMed

Sauer, Juergen; Chavaillaz, Alain; Wastell, David

2016-06-01

This work examined the effects of operators' exposure to various types of automation failures in training. Forty-five participants were trained for 3.5 h on a simulated process control environment. During training, participants either experienced a fully reliable, automatic fault repair facility (i.e. faults detected and correctly diagnosed), a misdiagnosis-prone one (i.e. faults detected but not correctly diagnosed) or a miss-prone one (i.e. faults not detected). One week after training, participants were tested for 3 h, experiencing two types of automation failures (misdiagnosis, miss). The results showed that automation bias was very high when operators trained on miss-prone automation encountered a failure of the diagnostic system. Operator errors resulting from automation bias were much higher when automation misdiagnosed a fault than when it missed one. Differences in trust levels that were instilled by the different training experiences disappeared during the testing session. Practitioner Summary: The experience of automation failures during training has some consequences. A greater potential for operator errors may be expected when an automatic system failed to diagnose a fault than when it failed to detect one.

(Semi-)Automated landform mapping of the alpine valley Gradental (Austria) based on LiDAR data

NASA Astrophysics Data System (ADS)

Strasser, T.; Eisank, C.

2012-04-01

Alpine valleys are typically characterised as complex, hierarchical structured systems with rapid landform changes. Detection of landform changes can be supported by automated geomorphological mapping. Especially, the analysis over short time scales require a method for standardised, unbiased geomorphological map reproduction, which is delivered by automated mapping techniques. In general, digital geomorphological mapping is a challenging task, since knowledge about landforms with respect to their natural boundaries as well as their hierarchical and scaling relationships, has to be integrated in an objective way. A combination of very-high spatial resolution data (VHSR) such as LiDAR and new methods like object based image analysis (OBIA) allow for a more standardised production of geomorphological maps. In OBIA the processing units are spatially configured objects that are created by multi-scale segmentation. Therefore, not only spectral information can be used for assigning the objects to geomorphological classes, but also spatial and topological properties can be exploited. In this study we focus on the detection of landforms, especially bedrock sediment deposits (alluvion, debris cone, talus, moraine, rockglacier), as well as glaciers. The study site Gradental [N 46°58'29.1"/ E 12°48'53.8"] is located in the Schobergruppe (Austria, Carinthia) and is characterised by heterogenic geology conditions and high process activity. The area is difficult to access and dominated by steep slopes, thus hindering a fast and detailed geomorphological field mapping. Landforms are identified using aerial and terrestrial LiDAR data (1 m spatial resolution). These DEMs are analysed by an object based hierarchical approach, which is structured in three main steps. The first step is to define occurring landforms by basic land surface parameters (LSPs), topology and hierarchy relations. Based on those definitions a semantic model is created. Secondly, a multi-scale segmentation is performed on a three-band LSP that integrates slope, aspect and plan curvature, which expresses the driving forces of geomorphological processes. In the third step, the generated multi-level object structures are classified in order to produce the geomorphological map. The classification rules are derived from the semantic model. Due to landform type-specific scale dependencies of LSPs, the values of LSPs used in the classification are calculated in a multi-scale manner by constantly enlarging the size of the moving window. In addition, object form properties (density, compactness, rectangular fit) are utilised as additional information for landform characterisation. Validation of classification is performed by intersecting a visually interpreted reference map with the classification output map and calculating accuracy matrices. Validation shows an overall accuracy of 78.25 % and a Kappa of 0.65. The natural borders of landforms can be easily detected by the use of slope, aspect and plan curvature. This study illustrates the potential of OBIA for a more standardised and automated mapping of surface units (landforms, landcover). Therefore, the presented methodology features a prospective automated geomorphological mapping approach for alpine regions.

Border preserving skin lesion segmentation

NASA Astrophysics Data System (ADS)

Kamali, Mostafa; Samei, Golnoosh

2008-03-01

Melanoma is a fatal cancer with a growing incident rate. However it could be cured if diagnosed in early stages. The first step in detecting melanoma is the separation of skin lesion from healthy skin. There are particular features associated with a malignant lesion whose successful detection relies upon accurately extracted borders. We propose a two step approach. First, we apply K-means clustering method (to 3D RGB space) that extracts relatively accurate borders. In the second step we perform an extra refining step for detecting the fading area around some lesions as accurately as possible. Our method has a number of novelties. Firstly as the clustering method is directly applied to the 3D color space, we do not overlook the dependencies between different color channels. In addition, it is capable of extracting fine lesion borders up to pixel level in spite of the difficulties associated with fading areas around the lesion. Performing clustering in different color spaces reveals that 3D RGB color space is preferred. The application of the proposed algorithm to an extensive data-base of skin lesions shows that its performance is superior to that of existing methods both in terms of accuracy and computational complexity.

Assessment of automated disease detection in diabetic retinopathy screening using two-field photography.

PubMed

Goatman, Keith; Charnley, Amanda; Webster, Laura; Nussey, Stephen

2011-01-01

To assess the performance of automated disease detection in diabetic retinopathy screening using two field mydriatic photography. Images from 8,271 sequential patient screening episodes from a South London diabetic retinopathy screening service were processed by the Medalytix iGrading™ automated grading system. For each screening episode macular-centred and disc-centred images of both eyes were acquired and independently graded according to the English national grading scheme. Where discrepancies were found between the automated result and original manual grade, internal and external arbitration was used to determine the final study grades. Two versions of the software were used: one that detected microaneurysms alone, and one that detected blot haemorrhages and exudates in addition to microaneurysms. Results for each version were calculated once using both fields and once using the macula-centred field alone. Of the 8,271 episodes, 346 (4.2%) were considered unassessable. Referable disease was detected in 587 episodes (7.1%). The sensitivity of the automated system for detecting unassessable images ranged from 97.4% to 99.1% depending on configuration. The sensitivity of the automated system for referable episodes ranged from 98.3% to 99.3%. All the episodes that included proliferative or pre-proliferative retinopathy were detected by the automated system regardless of configuration (192/192, 95% confidence interval 98.0% to 100%). If implemented as the first step in grading, the automated system would have reduced the manual grading effort by between 2,183 and 3,147 patient episodes (26.4% to 38.1%). Automated grading can safely reduce the workload of manual grading using two field, mydriatic photography in a routine screening service.

Strategies for rare-event detection: an approach for automated fetal cell detection in maternal blood.

PubMed Central

Oosterwijk, J C; Knepflé, C F; Mesker, W E; Vrolijk, H; Sloos, W C; Pattenier, H; Ravkin, I; van Ommen, G J; Kanhai, H H; Tanke, H J

1998-01-01

This article explores the feasibility of the use of automated microscopy and image analysis to detect the presence of rare fetal nucleated red blood cells (NRBCs) circulating in maternal blood. The rationales for enrichment and for automated image analysis for "rare-event" detection are reviewed. We also describe the application of automated image analysis to 42 maternal blood samples, using a protocol consisting of one-step enrichment followed by immunocytochemical staining for fetal hemoglobin (HbF) and FISH for X- and Y-chromosomal sequences. Automated image analysis consisted of multimode microscopy and subsequent visual evaluation of image memories containing the selected objects. The FISH results were compared with the results of conventional karyotyping of the chorionic villi. By use of manual screening, 43% of the slides were found to be positive (>=1 NRBC), with a mean number of 11 NRBCs (range 1-40). By automated microscopy, 52% were positive, with on average 17 NRBCs (range 1-111). There was a good correlation between both manual and automated screening, but the NRBC yield from automated image analysis was found to be superior to that from manual screening (P=.0443), particularly when the NRBC count was >15. Seven (64%) of 11 XY fetuses were correctly diagnosed by FISH analysis of automatically detected cells, and all discrepancies were restricted to the lower cell-count range. We believe that automated microscopy and image analysis reduce the screening workload, are more sensitive than manual evaluation, and can be used to detect rare HbF-containing NRBCs in maternal blood. PMID:9837832

Enhancement of the volcanogenic "bromine explosion" via reactive nitrogen chemistry (Kīlauea volcano, Hawai'i)

NASA Astrophysics Data System (ADS)

Salerno, G. G.; Oppenheimer, C.; Tsanev, V. I.; Sutton, A. J.; Roberts, T. J.; Elias, T.

2010-04-01

Since the first detection of bromine monoxide in volcanic plumes attention has focused on the atmospheric synthesis and impact of volcanogenic reactive halogens. We report here new measurements of BrO in the volcanic plume emitted from Kīlauea volcano - the first time reactive halogens have been observed in emissions from a hotspot volcano. Observations were carried out by ground-based Differential Optical Absorption Spectroscopy in 2007 and 2008 at Pu'u'O'o crater, and at the 2008 magmatic vent that opened within Halema'uma'u crater. BrO was readily detected in the Halema'uma'u plume (average column amount of 3×1015 molec cm-2) and its abundance was strongly correlated with that of SO2. However, anticorrelation between NO2 and SO2 (and BrO) abundances in the same plume strongly suggest an active role of NOx in reactive halogen chemistry. The calculated SO2/BrO molar ratio of ~1600 is comparable to observations at other volcanoes, although the BrO mixing ratio is roughly double that observed elsewhere. While BrO was not observed in the Pu'u'O'o plume this was probably merely a result of the detection limit of our measurements and based on understanding of the Summit and East Rift magmatic system we expect reactive halogens to be formed also in the Pu'u'O'o emissions. If this is correct then based on the long term SO2 flux from Pu'u'O'o we calculate that Kīlauea emits ~480 Mg yr-1 of reactive bromine and may thus represent an important source to the tropical Pacific troposphere.

Automated Detection of HONcode Website Conformity Compared to Manual Detection: An Evaluation.

PubMed

Boyer, Célia; Dolamic, Ljiljana

2015-06-02

To earn HONcode certification, a website must conform to the 8 principles of the HONcode of Conduct In the current manual process of certification, a HONcode expert assesses the candidate website using precise guidelines for each principle. In the scope of the European project KHRESMOI, the Health on the Net (HON) Foundation has developed an automated system to assist in detecting a website's HONcode conformity. Automated assistance in conducting HONcode reviews can expedite the current time-consuming tasks of HONcode certification and ongoing surveillance. Additionally, an automated tool used as a plugin to a general search engine might help to detect health websites that respect HONcode principles but have not yet been certified. The goal of this study was to determine whether the automated system is capable of performing as good as human experts for the task of identifying HONcode principles on health websites. Using manual evaluation by HONcode senior experts as a baseline, this study compared the capability of the automated HONcode detection system to that of the HONcode senior experts. A set of 27 health-related websites were manually assessed for compliance to each of the 8 HONcode principles by senior HONcode experts. The same set of websites were processed by the automated system for HONcode compliance detection based on supervised machine learning. The results obtained by these two methods were then compared. For the privacy criterion, the automated system obtained the same results as the human expert for 17 of 27 sites (14 true positives and 3 true negatives) without noise (0 false positives). The remaining 10 false negative instances for the privacy criterion represented tolerable behavior because it is important that all automatically detected principle conformities are accurate (ie, specificity [100%] is preferred over sensitivity [58%] for the privacy criterion). In addition, the automated system had precision of at least 75%, with a recall of more than 50% for contact details (100% precision, 69% recall), authority (85% precision, 52% recall), and reference (75% precision, 56% recall). The results also revealed issues for some criteria such as date. Changing the "document" definition (ie, using the sentence instead of whole document as a unit of classification) within the automated system resolved some but not all of them. Study results indicate concordance between automated and expert manual compliance detection for authority, privacy, reference, and contact details. Results also indicate that using the same general parameters for automated detection of each criterion produces suboptimal results. Future work to configure optimal system parameters for each HONcode principle would improve results. The potential utility of integrating automated detection of HONcode conformity into future search engines is also discussed.

Automated Detection of HONcode Website Conformity Compared to Manual Detection: An Evaluation

PubMed Central

2015-01-01

Background To earn HONcode certification, a website must conform to the 8 principles of the HONcode of Conduct In the current manual process of certification, a HONcode expert assesses the candidate website using precise guidelines for each principle. In the scope of the European project KHRESMOI, the Health on the Net (HON) Foundation has developed an automated system to assist in detecting a website’s HONcode conformity. Automated assistance in conducting HONcode reviews can expedite the current time-consuming tasks of HONcode certification and ongoing surveillance. Additionally, an automated tool used as a plugin to a general search engine might help to detect health websites that respect HONcode principles but have not yet been certified. Objective The goal of this study was to determine whether the automated system is capable of performing as good as human experts for the task of identifying HONcode principles on health websites. Methods Using manual evaluation by HONcode senior experts as a baseline, this study compared the capability of the automated HONcode detection system to that of the HONcode senior experts. A set of 27 health-related websites were manually assessed for compliance to each of the 8 HONcode principles by senior HONcode experts. The same set of websites were processed by the automated system for HONcode compliance detection based on supervised machine learning. The results obtained by these two methods were then compared. Results For the privacy criterion, the automated system obtained the same results as the human expert for 17 of 27 sites (14 true positives and 3 true negatives) without noise (0 false positives). The remaining 10 false negative instances for the privacy criterion represented tolerable behavior because it is important that all automatically detected principle conformities are accurate (ie, specificity [100%] is preferred over sensitivity [58%] for the privacy criterion). In addition, the automated system had precision of at least 75%, with a recall of more than 50% for contact details (100% precision, 69% recall), authority (85% precision, 52% recall), and reference (75% precision, 56% recall). The results also revealed issues for some criteria such as date. Changing the “document” definition (ie, using the sentence instead of whole document as a unit of classification) within the automated system resolved some but not all of them. Conclusions Study results indicate concordance between automated and expert manual compliance detection for authority, privacy, reference, and contact details. Results also indicate that using the same general parameters for automated detection of each criterion produces suboptimal results. Future work to configure optimal system parameters for each HONcode principle would improve results. The potential utility of integrating automated detection of HONcode conformity into future search engines is also discussed. PMID:26036669

Automatic quantitative analysis of in-stent restenosis using FD-OCT in vivo intra-arterial imaging.

PubMed

Mandelias, Kostas; Tsantis, Stavros; Spiliopoulos, Stavros; Katsakiori, Paraskevi F; Karnabatidis, Dimitris; Nikiforidis, George C; Kagadis, George C

2013-06-01

A new segmentation technique is implemented for automatic lumen area extraction and stent strut detection in intravascular optical coherence tomography (OCT) images for the purpose of quantitative analysis of in-stent restenosis (ISR). In addition, a user-friendly graphical user interface (GUI) is developed based on the employed algorithm toward clinical use. Four clinical datasets of frequency-domain OCT scans of the human femoral artery were analyzed. First, a segmentation method based on fuzzy C means (FCM) clustering and wavelet transform (WT) was applied toward inner luminal contour extraction. Subsequently, stent strut positions were detected by utilizing metrics derived from the local maxima of the wavelet transform into the FCM membership function. The inner lumen contour and the position of stent strut were extracted with high precision. Compared to manual segmentation by an expert physician, the automatic lumen contour delineation had an average overlap value of 0.917 ± 0.065 for all OCT images included in the study. The strut detection procedure achieved an overall accuracy of 93.80% and successfully identified 9.57 ± 0.5 struts for every OCT image. Processing time was confined to approximately 2.5 s per OCT frame. A new fast and robust automatic segmentation technique combining FCM and WT for lumen border extraction and strut detection in intravascular OCT images was designed and implemented. The proposed algorithm integrated in a GUI represents a step forward toward the employment of automated quantitative analysis of ISR in clinical practice.

Understanding reliance on automation: effects of error type, error distribution, age and experience

PubMed Central

Sanchez, Julian; Rogers, Wendy A.; Fisk, Arthur D.; Rovira, Ericka

2015-01-01

An obstacle detection task supported by “imperfect” automation was used with the goal of understanding the effects of automation error types and age on automation reliance. Sixty younger and sixty older adults interacted with a multi-task simulation of an agricultural vehicle (i.e. a virtual harvesting combine). The simulator included an obstacle detection task and a fully manual tracking task. A micro-level analysis provided insight into the way reliance patterns change over time. The results indicated that there are distinct patterns of reliance that develop as a function of error type. A prevalence of automation false alarms led participants to under-rely on the automation during alarm states while over relying on it during non-alarms states. Conversely, a prevalence of automation misses led participants to over-rely on automated alarms and under-rely on the automation during non-alarm states. Older adults adjusted their behavior according to the characteristics of the automation similarly to younger adults, although it took them longer to do so. The results of this study suggest the relationship between automation reliability and reliance depends on the prevalence of specific errors and on the state of the system. Understanding the effects of automation detection criterion settings on human-automation interaction can help designers of automated systems make predictions about human behavior and system performance as a function of the characteristics of the automation. PMID:25642142

Understanding reliance on automation: effects of error type, error distribution, age and experience.

PubMed

Sanchez, Julian; Rogers, Wendy A; Fisk, Arthur D; Rovira, Ericka

2014-03-01

An obstacle detection task supported by "imperfect" automation was used with the goal of understanding the effects of automation error types and age on automation reliance. Sixty younger and sixty older adults interacted with a multi-task simulation of an agricultural vehicle (i.e. a virtual harvesting combine). The simulator included an obstacle detection task and a fully manual tracking task. A micro-level analysis provided insight into the way reliance patterns change over time. The results indicated that there are distinct patterns of reliance that develop as a function of error type. A prevalence of automation false alarms led participants to under-rely on the automation during alarm states while over relying on it during non-alarms states. Conversely, a prevalence of automation misses led participants to over-rely on automated alarms and under-rely on the automation during non-alarm states. Older adults adjusted their behavior according to the characteristics of the automation similarly to younger adults, although it took them longer to do so. The results of this study suggest the relationship between automation reliability and reliance depends on the prevalence of specific errors and on the state of the system. Understanding the effects of automation detection criterion settings on human-automation interaction can help designers of automated systems make predictions about human behavior and system performance as a function of the characteristics of the automation.

Border effect-based precise measurement of any frequency signal

NASA Astrophysics Data System (ADS)

Bai, Li-Na; Ye, Bo; Xuan, Mei-Na; Jin, Yu-Zhen; Zhou, Wei

2015-12-01

Limited detection resolution leads to fuzzy areas during the measurement, and the discrimination of the border of a fuzzy area helps to use the resolution stability. In this way, measurement precision is greatly improved, hence this phenomenon is named the border effect. The resolution fuzzy area and its application should be studied to realize high-resolution measurement. During the measurement of any frequency signal, the fuzzy areas of phase-coincidence detection are always discrete and irregular. In this paper the difficulty in capturing the border information of discrete fuzzy areas is overcome and extra-high resolution measurement is implemented. Measurement precision of any frequency-signal can easily reach better than 1 × 10-11/s in a wide range of frequencies, showing the great importance of the border effect. An in-depth study of this issue has great significance for frequency standard comparison, signal processing, telecommunication, and fundamental subjects. Project supported by the National Natural Science Foundation of China (Grant Nos. 10978017 and 61201288), the Natural Science Foundation of Research Plan Projects of Shaanxi Province, China (Grant No. 2014JM2-6128), and the Sino-Poland Science and Technology Cooperation Projects (Grant No. 36-33).

THE BINDING OF COCAINE TO CYCLODEXTRINS. (R826653)

EPA Science Inventory

Abstract

Cocaine binds into -cyclodextrin, but not detectably into

Load-Differential Features for Automated Detection of Fatigue Cracks Using Guided Waves (Preprint)

DTIC Science & Technology

2011-11-01

AFRL-RX-WP-TP-2011-4363 LOAD-DIFFERENTIAL FEATURES FOR AUTOMATED DETECTION OF FATIGUE CRACKS USING GUIDED WAVES (PREPRINT) Jennifer E...AUTOMATED DETECTION OF FATIGUE CRACKS USING GUIDED WAVES (PREPRINT) 5a. CONTRACT NUMBER FA8650-09-C-5206 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER...tensile loads open fatigue cracks and thus enhance their detectability using ultrasonic methods. Here we introduce a class of load-differential methods

Complete Genomic Characterization of Three Tick-Borne Encephalitis Viruses Detected Along the China-North Korea Border, 2011.

PubMed

He, Xiaoxia; Zhao, Junwei; Fu, Shihong; Yao, Lisi; Gao, Xiaoyan; Liu, Yan; He, Ying; Liang, Guodong; Wang, Huanyu

2018-05-09

Tick-borne encephalitis virus (TBEV) causes neurological infections with serious sequelae in Europe and Northeast Asia. In China, the major epidemic areas are along the borders with Russia and North Korea. Although several TBEV isolates have been reported, the biological characteristics of the Chinese strains, especially those along the China-North Korea border, are unclear. In this study, we detected seven TBEV fragment sequences in 602 adult Dermacentor silvarum collected in the Changbai Mountain area of Jilin Province on the China-North Korea border and characterized the genome of three TBEV strains (JLCB11-08, JLCB11-35, and JLCB11-40). These three TBEV strains belong to the TBEV-Far Eastern (TBEV-FE) genotype and clustered most closely with the Svetlogorie and Kavalerovo strains from Russia. In addition, the TBEV strains from Northeast China clustered geographically within the TBEV-FE subtype branch. These findings will facilitate further research on the distinct genetic groupings of TBEV strains in China.

Stakeholder identification of advanced technology opportunities at international ports of entry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parker, S.K.; Icerman, L.

As part of the Advanced Technologies for International and Intermodal Ports of Entry (ATIPE) Project, a diverse group of stakeholders was engaged to help identify problems experienced at inland international border crossings, particularly those at the US-Mexican border. The fundamental issue at international ports of entry is reducing transit time through the required documentation and inspection processes. Examples of other issues or problems, typically manifested as time delays at border crossings, repeatedly mentioned by stakeholders include: (1) lack of document standardization; (2) failure to standardize inspection processes; (3) inadequate information and communications systems; (4) manual fee and tariff collection; (5)more » inconsistency of processes and procedures; and (6) suboptimal cooperation among governmental agencies. Most of these issues can be addressed to some extent by the development of advanced technologies with the objective of allowing ports of entry to become more efficient while being more effective. Three categories of technologies were unambiguously of high priority to port of entry stakeholders: (1) automated documentation; (2) systems integration; and (3) vehicle and cargo tracking. Together, these technologies represent many of the technical components necessary for pre-clearance of freight approaching international ports of entry. Integration of vehicle and cargo tracking systems with port of entry information and communications systems, as well as existing industry legacy systems, should further enable border crossings to be accomplished consistently with optimal processing times.« less

Detection and severity classification of extracardiac interference in {sup 82}Rb PET myocardial perfusion imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Orton, Elizabeth J., E-mail: eorton@physics.carleton.ca; Kemp, Robert A. de; Glenn Wells, R.

2014-10-15

Purpose: Myocardial perfusion imaging (MPI) is used for diagnosis and prognosis of coronary artery disease. When MPI studies are performed with positron emission tomography (PET) and the radioactive tracer rubidium-82 chloride ({sup 82}Rb), a small but non-negligible fraction of studies (∼10%) suffer from extracardiac interference: high levels of tracer uptake in structures adjacent to the heart which mask the true cardiac tracer uptake. At present, there are no clinically available options for automated detection or correction of this problem. This work presents an algorithm that detects and classifies the severity of extracardiac interference in {sup 82}Rb PET MPI images andmore » reports the accuracy and failure rate of the method. Methods: A set of 200 {sup 82}Rb PET MPI images were reviewed by a trained nuclear cardiologist and interference severity reported on a four-class scale, from absent to severe. An automated algorithm was developed that compares uptake at the external border of the myocardium to three thresholds, separating the four interference severity classes. A minimum area of interference was required, and the search region was limited to that facing the stomach wall and spleen. Maximizing concordance (Cohen’s Kappa) and minimizing failure rate for the set of 200 clinician-read images were used to find the optimal population-based constants defining search limit and minimum area parameters and the thresholds for the algorithm. Tenfold stratified cross-validation was used to find optimal thresholds and report accuracy measures (sensitivity, specificity, and Kappa). Results: The algorithm was capable of detecting interference with a mean [95% confidence interval] sensitivity/specificity/Kappa of 0.97 [0.94, 1.00]/0.82 [0.66, 0.98]/0.79 [0.65, 0.92], and a failure rate of 1.0% ± 0.2%. The four-class overall Kappa was 0.72 [0.64, 0.81]. Separation of mild versus moderate-or-greater interference was performed with good accuracy (sensitivity/specificity/Kappa = 0.92 [0.86, 0.99]/0.86 [0.71, 1.00]/0.78 [0.64, 0.92]), while separation of moderate versus severe interference severity classes showed reduced sensitivity/Kappa but little change in specificity (sensitivity/specificity/Kappa = 0.83 [0.77, 0.88]/0.82 [0.77, 0.88]/0.65 [0.60, 0.70]). Specificity was greater than sensitivity for all interference classes. Algorithm execution time was <1 min. Conclusions: The algorithm produced here has a low failure rate and high accuracy for detection of extracardiac interference in {sup 82}Rb PET MPI scans. It provides a fast, reliable, automated method for assessing severity of extracardiac interference.« less

Effects of Vegetated Field Borders on Arthropods in Cotton Fields in Eastern North Carolina

PubMed Central

Outward, Randy; Sorenson, Clyde E.; Bradley, J. R.

2008-01-01

The influence, if any, of 5m wide, feral, herbaceous field borders on pest and beneficial arthropods in commercial cotton, Gossypium hirsutum (L.) (Malvales: Malvaceae), fields was measured through a variety of sampling techniques over three years. In each year, 5 fields with managed, feral vegetation borders and five fields without such borders were examined. Sampling was stratified from the field border or edge in each field in an attempt to elucidate any edge effects that might have occurred. Early season thrips populations appeared to be unaffected by the presence of a border. Pitfall sampling disclosed no differences in ground-dwelling predaceous arthropods but did detect increased populations of crickets around fields with borders. Cotton aphid (Aphis gossypii Glover) (Hemiptera: Aphididae) populations were too low during the study to adequately assess border effects. Heliothines, Heliothis virescens (F.) and Helicoverpa zea (Boddie) (Lepidoptera: Noctuidae), egg numbers and damage rates were largely unaffected by the presence or absence of a border, although in one instance egg numbers were significantly lower in fields with borders. Overall, foliage-dwelling predaceous arthropods were somewhat more abundant in fields with borders than in fields without borders. Tarnished plant bugs, Lygus lineolaris (Palisot de Beauvois) (Heteroptera: Miridae) were significantly more abundant in fields with borders, but stink bugs, Acrosternum hilare (Say), and Euschistus servus (Say) (Hemiptera: Pentatomidae) numbers appeared to be largely unaffected by border treatment. Few taxa clearly exhibited distributional edge effects relative to the presence or absence of border vegetation. Field borders like those examined in this study likely will have little impact on insect pest management in cotton under current insect management regimens. PMID:20345293

A new framework for analysing automated acoustic species-detection data: occupancy estimation and optimization of recordings post-processing

USGS Publications Warehouse

Chambert, Thierry A.; Waddle, J. Hardin; Miller, David A.W.; Walls, Susan; Nichols, James D.

2018-01-01

The development and use of automated species-detection technologies, such as acoustic recorders, for monitoring wildlife are rapidly expanding. Automated classification algorithms provide a cost- and time-effective means to process information-rich data, but often at the cost of additional detection errors. Appropriate methods are necessary to analyse such data while dealing with the different types of detection errors.We developed a hierarchical modelling framework for estimating species occupancy from automated species-detection data. We explore design and optimization of data post-processing procedures to account for detection errors and generate accurate estimates. Our proposed method accounts for both imperfect detection and false positive errors and utilizes information about both occurrence and abundance of detections to improve estimation.Using simulations, we show that our method provides much more accurate estimates than models ignoring the abundance of detections. The same findings are reached when we apply the methods to two real datasets on North American frogs surveyed with acoustic recorders.When false positives occur, estimator accuracy can be improved when a subset of detections produced by the classification algorithm is post-validated by a human observer. We use simulations to investigate the relationship between accuracy and effort spent on post-validation, and found that very accurate occupancy estimates can be obtained with as little as 1% of data being validated.Automated monitoring of wildlife provides opportunity and challenges. Our methods for analysing automated species-detection data help to meet key challenges unique to these data and will prove useful for many wildlife monitoring programs.

An Automated Energy Detection Algorithm Based on Kurtosis-Histogram Excision

DTIC Science & Technology

2018-01-01

ARL-TR-8269 ● JAN 2018 US Army Research Laboratory An Automated Energy Detection Algorithm Based on Kurtosis-Histogram Excision...needed. Do not return it to the originator. ARL-TR-8269 ● JAN 2018 US Army Research Laboratory An Automated Energy Detection...collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources

Information Analysis Methodology for Border Security Deployment Prioritization and Post Deployment Evaluation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Booker, Paul M.; Maple, Scott A.

2010-06-08

Due to international commerce, cross-border conflicts, and corruption, a holistic, information driven, approach to border security is required to best understand how resources should be applied to affect sustainable improvements in border security. The ability to transport goods and people by land, sea, and air across international borders with relative ease for legitimate commercial purposes creates a challenging environment to detect illicit smuggling activities that destabilize national level border security. Smuggling activities operated for profit or smuggling operations driven by cross border conflicts where militant or terrorist organizations facilitate the transport of materials and or extremists to advance a causemore » add complexity to smuggling interdiction efforts. Border security efforts are further hampered when corruption thwarts interdiction efforts or reduces the effectiveness of technology deployed to enhance border security. These issues necessitate the implementation of a holistic approach to border security that leverages all available data. Large amounts of information found in hundreds of thousands of documents can be compiled to assess national or regional borders to identify variables that influence border security. Location data associated with border topics of interest may be extracted and plotted to better characterize the current border security environment for a given country or region. This baseline assessment enables further analysis, but also documents the initial state of border security that can be used to evaluate progress after border security improvements are made. Then, border security threats are prioritized via a systems analysis approach. Mitigation factors to address risks can be developed and evaluated against inhibiting factor such as corruption. This holistic approach to border security helps address the dynamic smuggling interdiction environment where illicit activities divert to a new location that provides less resistance to smuggling activities after training or technology is deployed at a given location. This paper will present an approach to holistic border security information analysis.« less

Discharge measurement in tidally affected channels during a hydrographic estuarine survey of Sabine Lake, Texas

USGS Publications Warehouse

Dunn, David D.; Solis, R.S.; Ockerman, D.J.

1997-01-01

A hydrographic survey of Sabine Lake, a broad, shallow estuary lying on the Texas-Louisiana border, was conducted in June 1996 to help address questions relating to potential environmental effects of future water demands in Texas. The use of a variety of new instruments in this study is one means by which automation is improving efficiency and effectiveness of these efforts by increasing the quality and quantity of data collected.

Tunnel Detection Using Seismic Methods

NASA Astrophysics Data System (ADS)

Miller, R.; Park, C. B.; Xia, J.; Ivanov, J.; Steeples, D. W.; Ryden, N.; Ballard, R. F.; Llopis, J. L.; Anderson, T. S.; Moran, M. L.; Ketcham, S. A.

2006-05-01

Surface seismic methods have shown great promise for use in detecting clandestine tunnels in areas where unauthorized movement beneath secure boundaries have been or are a matter of concern for authorities. Unauthorized infiltration beneath national borders and into or out of secure facilities is possible at many sites by tunneling. Developments in acquisition, processing, and analysis techniques using multi-channel seismic imaging have opened the door to a vast number of near-surface applications including anomaly detection and delineation, specifically tunnels. Body waves have great potential based on modeling and very preliminary empirical studies trying to capitalize on diffracted energy. A primary limitation of all seismic energy is the natural attenuation of high-frequency energy by earth materials and the difficulty in transmitting a high- amplitude source pulse with a broad spectrum above 500 Hz into the earth. Surface waves have shown great potential since the development of multi-channel analysis methods (e.g., MASW). Both shear-wave velocity and backscatter energy from surface waves have been shown through modeling and empirical studies to have great promise in detecting the presence of anomalies, such as tunnels. Success in developing and evaluating various seismic approaches for detecting tunnels relies on investigations at known tunnel locations, in a variety of geologic settings, employing a wide range of seismic methods, and targeting a range of uniquely different tunnel geometries, characteristics, and host lithologies. Body-wave research at the Moffat tunnels in Winter Park, Colorado, provided well-defined diffraction-looking events that correlated with the subsurface location of the tunnel complex. Natural voids related to karst have been studied in Kansas, Oklahoma, Alabama, and Florida using shear-wave velocity imaging techniques based on the MASW approach. Manmade tunnels, culverts, and crawl spaces have been the target of multi-modal analysis in Kansas and California. Clandestine tunnels used for illegal entry into the U.S. from Mexico were studied at two different sites along the southern border of California. All these studies represent the empirical basis for suggesting surface seismic has a significant role to play in tunnel detection and that methods are under development and very nearly at hand that will provide an effective tool in appraising and maintaining parameter security. As broadband sources, gravity-coupled towed spreads, and automated analysis software continues to make advancements, so does the applicability of routine deployment of seismic imaging systems that can be operated by technicians with interpretation aids for nearly real-time target selection. Key to making these systems commercial is the development of enhanced imaging techniques in geologically noisy areas and highly variable surface terrain.

[Research and Design of a System for Detecting Automated External Defbrillator Performance Parameters].

PubMed

Wang, Kewu; Xiao, Shengxiang; Jiang, Lina; Hu, Jingkai

2017-09-30

In order to regularly detect the performance parameters of automated external defibrillator (AED), to make sure it is safe before using the instrument, research and design of a system for detecting automated external defibrillator performance parameters. According to the research of the characteristics of its performance parameters, combing the STM32's stability and high speed with PWM modulation control, the system produces a variety of ECG normal and abnormal signals through the digital sampling methods. Completed the design of the hardware and software, formed a prototype. This system can accurate detect automated external defibrillator discharge energy, synchronous defibrillation time, charging time and other key performance parameters.

Automated 3D segmentation of intraretinal layers from optic nerve head optical coherence tomography images

NASA Astrophysics Data System (ADS)

Antony, Bhavna J.; Abràmoff, Michael D.; Lee, Kyungmoo; Sonkova, Pavlina; Gupta, Priya; Kwon, Young; Niemeijer, Meindert; Hu, Zhihong; Garvin, Mona K.

2010-03-01

Optical coherence tomography (OCT), being a noninvasive imaging modality, has begun to find vast use in the diagnosis and management of ocular diseases such as glaucoma, where the retinal nerve fiber layer (RNFL) has been known to thin. Furthermore, the recent availability of the considerably larger volumetric data with spectral-domain OCT has increased the need for new processing techniques. In this paper, we present an automated 3-D graph-theoretic approach for the segmentation of 7 surfaces (6 layers) of the retina from 3-D spectral-domain OCT images centered on the optic nerve head (ONH). The multiple surfaces are detected simultaneously through the computation of a minimum-cost closed set in a vertex-weighted graph constructed using edge/regional information, and subject to a priori determined varying surface interaction and smoothness constraints. The method also addresses the challenges posed by presence of the large blood vessels and the optic disc. The algorithm was compared to the average manual tracings of two observers on a total of 15 volumetric scans, and the border positioning error was found to be 7.25 +/- 1.08 μm and 8.94 +/- 3.76 μm for the normal and glaucomatous eyes, respectively. The RNFL thickness was also computed for 26 normal and 70 glaucomatous scans where the glaucomatous eyes showed a significant thinning (p < 0.01, mean thickness 73.7 +/- 32.7 μm in normal eyes versus 60.4 +/- 25.2 μm in glaucomatous eyes).

Improved cancer diagnostics by different image processing techniques on OCT images

NASA Astrophysics Data System (ADS)

Kanawade, Rajesh; Lengenfelder, Benjamin; Marini Menezes, Tassiana; Hohmann, Martin; Kopfinger, Stefan; Hohmann, Tim; Grabiec, Urszula; Klämpfl, Florian; Gonzales Menezes, Jean; Waldner, Maximilian; Schmidt, Michael

2015-07-01

Optical-coherence tomography (OCT) is a promising non-invasive, high-resolution imaging modality which can be used for cancer diagnosis and its therapeutic assessment. However, speckle noise makes detection of cancer boundaries and image segmentation problematic and unreliable. Therefore, to improve the image analysis for a precise cancer border detection, the performance of different image processing algorithms such as mean, median, hybrid median filter and rotational kernel transformation (RKT) for this task is investigated. This is done on OCT images acquired from an ex-vivo human cancerous mucosa and in vitro by using cultivated tumour applied on organotypical hippocampal slice cultures. The preliminary results confirm that the border between the healthy and the cancer lesions can be identified precisely. The obtained results are verified with fluorescence microscopy. This research can improve cancer diagnosis and the detection of borders between healthy and cancerous tissue. Thus, it could also reduce the number of biopsies required during screening endoscopy by providing better guidance to the physician.

Computer-aided diagnostic approach of dermoscopy images acquiring relevant features

NASA Astrophysics Data System (ADS)

Castillejos-Fernández, H.; Franco-Arcega, A.; López-Ortega, O.

2016-09-01

In skin cancer detection, automated analysis of borders, colors, and structures of a lesion relies upon an accurate segmentation process and it is an important first step in any Computer-Aided Diagnosis (CAD) system. However, irregular and disperse lesion borders, low contrast, artifacts in images and variety of colors within the interest region make the problem difficult. In this paper, we propose an efficient approach of automatic classification which considers specific lesion features. First, for the selection of lesion skin we employ the segmentation algorithm W-FCM.1 Then, in the feature extraction stage we consider several aspects: the area of the lesion, which is calculated by correlating axes and we calculate the specific the value of asymmetry in both axes. For color analysis we employ an ensemble of clusterers including K-Means, Fuzzy K-Means and Kohonep maps, all of which estimate the presence of one or more colors defined in ABCD rule and the values for each of the segmented colors. Another aspect to consider is the type of structures that appear in the lesion Those are defined by using the ell-known GLCM method. During the classification stage we compare several methods in order to define if the lesion is benign or malignant. An important contribution of the current approach in segmentation-classification problem resides in the use of information from all color channels together, as well as the measure of each color in the lesion and the axes correlation. The segmentation and classification measures have been performed using sensibility, specificity, accuracy and AUC metric over a set of dermoscopy images from ISDIS data set

Automatic MRI 2D brain segmentation using graph searching technique.

PubMed

Pedoia, Valentina; Binaghi, Elisabetta

2013-09-01

Accurate and efficient segmentation of the whole brain in magnetic resonance (MR) images is a key task in many neuroscience and medical studies either because the whole brain is the final anatomical structure of interest or because the automatic extraction facilitates further analysis. The problem of segmenting brain MRI images has been extensively addressed by many researchers. Despite the relevant achievements obtained, automated segmentation of brain MRI imagery is still a challenging problem whose solution has to cope with critical aspects such as anatomical variability and pathological deformation. In the present paper, we describe and experimentally evaluate a method for segmenting brain from MRI images basing on two-dimensional graph searching principles for border detection. The segmentation of the whole brain over the entire volume is accomplished slice by slice, automatically detecting frames including eyes. The method is fully automatic and easily reproducible by computing the internal main parameters directly from the image data. The segmentation procedure is conceived as a tool of general applicability, although design requirements are especially commensurate with the accuracy required in clinical tasks such as surgical planning and post-surgical assessment. Several experiments were performed to assess the performance of the algorithm on a varied set of MRI images obtaining good results in terms of accuracy and stability. Copyright © 2012 John Wiley & Sons, Ltd.

Optical coherence tomography angiography in the management of age-related macular degeneration.

PubMed

Schneider, Eric W; Fowler, Samuel C

2018-05-01

Optical coherence tomography angiography (OCT-A) provides rapid, flow-based imaging of the retinal and choroidal vasculature in a noninvasive manner. This review contrasts this novel technique with conventional angiography and discusses its current uses and limitations in the management of age-related macular degeneration (AMD). Initial work with OCT-A has focused on its ability to identify choriocapillaris flow alterations in dry AMD and to sensitively detect choroidal neovascular membranes (CNVs) in neovascular AMD. Reduced choriocapillaris flow beyond the borders of geographic atrophy seen on OCT-A suggests a primary vascular cause in geographic atrophy. Longitudinal OCT-A analysis of CNV morphology has demonstrated the transition from an immature to mature CNV phenotype following treatment. Current clinical applications of OCT-A include identification of asymptomatic CNV and monitoring for CNV development in the setting of an acquired vitelliform lesion. OCT-A remains a promising diagnostic tool but one still very much in evolution. Larger studies will be needed to more accurately describe its sensitivity and specificity for CNV detection and to better characterize longitudinal CNV morphologic changes. Anticipated hardware and software updates including swept-source light sources, automated montaging, and manual adjustment of interscan timing should enhance the capabilities of OCT-A in the management of AMD.

The value of automated gel column agglutination technology in the identification of true inherited D blood types in massively transfused patients.

PubMed

Summers, Thomas; Johnson, Viviana V; Stephan, John P; Johnson, Gloria J; Leonard, George

2009-08-01

Massive transfusion of D- trauma patients in the combat setting involves the use of D+ red blood cells (RBCs) or whole blood along with suboptimal pretransfusion test result documentation. This presents challenges to the transfusion service of tertiary care military hospitals who ultimately receive these casualties because initial D typing results may only reflect the transfused RBCs. After patients are stabilized, mixed-field reaction results on D typing indicate the patient's true inherited D phenotype. This case series illustrates the utility of automated gel column agglutination in detecting mixed-field reactions in these patients. The transfusion service test results, including the automated gel column agglutination D typing results, of four massively transfused D- patients transfused D+ RBCs is presented. To test the sensitivity of the automated gel column agglutination method in detecting mixed-field agglutination reactions, a comparative analysis of three automated technologies using predetermined mixtures of D+ and D- RBCs is also presented. The automated gel column agglutination method detected mixed-field agglutination in D typing in all four patients and in the three prepared control specimens. The automated microwell tube method identified one of the three prepared control specimens as indeterminate, which was subsequently manually confirmed as a mixed-field reaction. The automated solid-phase method was unable to detect any mixed fields. The automated gel column agglutination method provides a sensitive means for detecting mixed-field agglutination reactions in the determination of the true inherited D phenotype of combat casualties transfused massive amounts of D+ RBCs.

Induction detection of concealed bulk banknotes

NASA Astrophysics Data System (ADS)

Fuller, Christopher; Chen, Antao

2012-06-01

The smuggling of bulk cash across borders is a serious issue that has increased in recent years. In an effort to curb the illegal transport of large numbers of paper bills, a detection scheme has been developed, based on the magnetic characteristics of bank notes. The results show that volumes of paper currency can be detected through common concealing materials such as plastics, cardboard, and fabrics making it a possible potential addition to border security methods. The detection scheme holds the potential of also reducing or eliminating false positives caused by metallic materials found in the vicinity, by observing the stark difference in received signals caused by metal and currency. The detection scheme holds the potential to detect for both the presence and number of concealed bulk notes, while maintaining the ability to reduce false positives caused by metal objects.

Real-time 3D reconstruction of road curvature in far look-ahead distance from analysis of image sequences

NASA Astrophysics Data System (ADS)

Behringer, Reinhold

1995-12-01

A system for visual road recognition in far look-ahead distance, implemented in the autonomous road vehicle VaMP (a passenger car), is described. Visual cues of a road in a video image are the bright lane markings and the edges formed at the road borders. In a distance of more than 100 m, the most relevant road cue is the homogeneous road area, limited by the two border edges. These cues can be detected by the image processing module KRONOS applying edge detection techniques and areal 2D segmentation based on resolution triangles (analogous to a resolution pyramid). An estimation process performs an update of a state vector, which describes spatial road shape and vehicle orientation relative to the road. This state vector is estimated every 40 ms by exploiting knowledge about the vehicle movement (spatio-temporal model of vehicle dynamics) and the road design rules (clothoidal segments). Kalman filter techniques are applied to obtain an optimal estimate of the state vector by evaluating the measurements of the road border positions in the image sequence taken by a set of CCD cameras. The road consists of segments with piecewise constant curvature parameters. The borders between these segments can be detected by applying methods which have been developed for detection of discontinuities during time-discrete measurements. The road recognition system has been tested in autonomous rides with VaMP on public Autobahnen in real traffic at speeds up to 130 km/h.

Automated System for Early Breast Cancer Detection in Mammograms

NASA Technical Reports Server (NTRS)

Bankman, Isaac N.; Kim, Dong W.; Christens-Barry, William A.; Weinberg, Irving N.; Gatewood, Olga B.; Brody, William R.

1993-01-01

The increasing demand on mammographic screening for early breast cancer detection, and the subtlety of early breast cancer signs on mammograms, suggest an automated image processing system that can serve as a diagnostic aid in radiology clinics. We present a fully automated algorithm for detecting clusters of microcalcifications that are the most common signs of early, potentially curable breast cancer. By using the contour map of the mammogram, the algorithm circumvents some of the difficulties encountered with standard image processing methods. The clinical implementation of an automated instrument based on this algorithm is also discussed.

The effect of JPEG compression on automated detection of microaneurysms in retinal images

NASA Astrophysics Data System (ADS)

Cree, M. J.; Jelinek, H. F.

2008-02-01

As JPEG compression at source is ubiquitous in retinal imaging, and the block artefacts introduced are known to be of similar size to microaneurysms (an important indicator of diabetic retinopathy) it is prudent to evaluate the effect of JPEG compression on automated detection of retinal pathology. Retinal images were acquired at high quality and then compressed to various lower qualities. An automated microaneurysm detector was run on the retinal images of various qualities of JPEG compression and the ability to predict the presence of diabetic retinopathy based on the detected presence of microaneurysms was evaluated with receiver operating characteristic (ROC) methodology. The negative effect of JPEG compression on automated detection was observed even at levels of compression sometimes used in retinal eye-screening programmes and these may have important clinical implications for deciding on acceptable levels of compression for a fully automated eye-screening programme.

Detecting the borders between coding and non-coding DNA regions in prokaryotes based on recursive segmentation and nucleotide doublets statistics

PubMed Central

2012-01-01

Background Detecting the borders between coding and non-coding regions is an essential step in the genome annotation. And information entropy measures are useful for describing the signals in genome sequence. However, the accuracies of previous methods of finding borders based on entropy segmentation method still need to be improved. Methods In this study, we first applied a new recursive entropic segmentation method on DNA sequences to get preliminary significant cuts. A 22-symbol alphabet is used to capture the differential composition of nucleotide doublets and stop codon patterns along three phases in both DNA strands. This process requires no prior training datasets. Results Comparing with the previous segmentation methods, the experimental results on three bacteria genomes, Rickettsia prowazekii, Borrelia burgdorferi and E.coli, show that our approach improves the accuracy for finding the borders between coding and non-coding regions in DNA sequences. Conclusions This paper presents a new segmentation method in prokaryotes based on Jensen-Rényi divergence with a 22-symbol alphabet. For three bacteria genomes, comparing to A12_JR method, our method raised the accuracy of finding the borders between protein coding and non-coding regions in DNA sequences. PMID:23282225

Complementary use of optical coherence tomography and 5-aminolevulinic acid induced fluorescent spectroscopy for diagnosis of neoplastic processes in cervix and vulva

NASA Astrophysics Data System (ADS)

Sapozhnikova, Veronika V.; Shakhova, Natalia M.; Kamensky, Vladislav A.; Kuranov, Roman V.; Loshenov, Victor B.; Petrova, Svetlana A.

2003-07-01

A new approach to improving the diagnostic value of optical methods is suggested, which is based on a complementary investigation of different optical parameters of biotissues. The aim of this paper is comparative study of the feasibility of two optical methods - fluorescence spectroscopy and optical coherence tomography - for visualization of borders of neoplastic processes in the uterine cervix and vulva. Fluorescence spectroscopy is based on the detection of biochemical and optical coherence tomography on backscattering properties in norm and pathological changes of tissues. By means of these optical methods changes in biochemical and morphological properties of tissues were investigated. A parallel analysis of these two optical methods and histology from the center of tumors and their optical borders was made. Thirteen female patients with neoplastic changes in uterine cervix and vulva were enrolled in this study. The borders of the tumor determined by optical methods (fluorescence spectroscopy and optical coherence tomography) are coinciding with the biopsy proved ones. In addition, OCT and fluorescence borders of tumor in the uterine cervix and vulva exceeds colposcopically detectable borders, the averaging difference 2 mm. In future optical methods would considerably enhance diagnostic accuracy of conventional methods used in oncogynecology.

Automated and Clinical Breast Imaging Reporting and Data System Density Measures Predict Risk for Screen-Detected and Interval Cancers: A Case-Control Study.

PubMed

Kerlikowske, Karla; Scott, Christopher G; Mahmoudzadeh, Amir P; Ma, Lin; Winham, Stacey; Jensen, Matthew R; Wu, Fang Fang; Malkov, Serghei; Pankratz, V Shane; Cummings, Steven R; Shepherd, John A; Brandt, Kathleen R; Miglioretti, Diana L; Vachon, Celine M

2018-06-05

In 30 states, women who have had screening mammography are informed of their breast density on the basis of Breast Imaging Reporting and Data System (BI-RADS) density categories estimated subjectively by radiologists. Variation in these clinical categories across and within radiologists has led to discussion about whether automated BI-RADS density should be reported instead. To determine whether breast cancer risk and detection are similar for automated and clinical BI-RADS density measures. Case-control. San Francisco Mammography Registry and Mayo Clinic. 1609 women with screen-detected cancer, 351 women with interval invasive cancer, and 4409 matched control participants. Automated and clinical BI-RADS density assessed on digital mammography at 2 time points from September 2006 to October 2014, interval and screen-detected breast cancer risk, and mammography sensitivity. Of women whose breast density was categorized by automated BI-RADS more than 6 months to 5 years before diagnosis, those with extremely dense breasts had a 5.65-fold higher interval cancer risk (95% CI, 3.33 to 9.60) and a 1.43-fold higher screen-detected risk (CI, 1.14 to 1.79) than those with scattered fibroglandular densities. Associations of interval and screen-detected cancer with clinical BI-RADS density were similar to those with automated BI-RADS density, regardless of whether density was measured more than 6 months to less than 2 years or 2 to 5 years before diagnosis. Automated and clinical BI-RADS density measures had similar discriminatory accuracy, which was higher for interval than screen-detected cancer (c-statistics: 0.70 vs. 0.62 [P < 0.001] and 0.72 vs. 0.62 [P < 0.001], respectively). Mammography sensitivity was similar for automated and clinical BI-RADS categories: fatty, 93% versus 92%; scattered fibroglandular densities, 90% versus 90%; heterogeneously dense, 82% versus 78%; and extremely dense, 63% versus 64%, respectively. Neither automated nor clinical BI-RADS density was assessed on tomosynthesis, an emerging breast screening method. Automated and clinical BI-RADS density similarly predict interval and screen-detected cancer risk, suggesting that either measure may be used to inform women of their breast density. National Cancer Institute.

Fully Automated Sunspot Detection and Classification Using SDO HMI Imagery in MATLAB

DTIC Science & Technology

2014-03-27

FULLY AUTOMATED SUNSPOT DETECTION AND CLASSIFICATION USING SDO HMI IMAGERY IN MATLAB THESIS Gordon M. Spahr, Second Lieutenant, USAF AFIT-ENP-14-M-34...CLASSIFICATION USING SDO HMI IMAGERY IN MATLAB THESIS Presented to the Faculty Department of Engineering Physics Graduate School of Engineering and Management Air...DISTRIUBUTION UNLIMITED. AFIT-ENP-14-M-34 FULLY AUTOMATED SUNSPOT DETECTION AND CLASSIFICATION USING SDO HMI IMAGERY IN MATLAB Gordon M. Spahr, BS Second

Research on regional intrusion prevention and control system based on target tracking

NASA Astrophysics Data System (ADS)

Liu, Yanfei; Wang, Jieling; Jiang, Ke; He, Yanhui; Wu, Zhilin

2017-08-01

In view of the fact that China’s border is very long and the border prevention and control measures are single, we designed a regional intrusion prevention and control system which based on target-tracking. The system consists of four parts: solar panel, radar, electro-optical equipment, unmanned aerial vehicle and intelligent tracking platform. The solar panel provides independent power for the entire system. The radar detects the target in real time and realizes the high precision positioning of suspicious targets, then through the linkage of electro-optical equipment, it can achieve full-time automatic precise tracking of targets. When the target appears within the range of detection, the drone will be launched to continue the tracking. The system is mainly to realize the full time, full coverage, whole process integration and active realtime control of the border area.

Detecting a trend change in cross-border epidemic transmission

NASA Astrophysics Data System (ADS)

Maeno, Yoshiharu

2016-09-01

A method for a system of Langevin equations is developed for detecting a trend change in cross-border epidemic transmission. The equations represent a standard epidemiological SIR compartment model and a meta-population network model. The method analyzes a time series of the number of new cases reported in multiple geographical regions. The method is applicable to investigating the efficacy of the implemented public health intervention in managing infectious travelers across borders. It is found that the change point of the probability of travel movements was one week after the WHO worldwide alert on the SARS outbreak in 2003. The alert was effective in managing infectious travelers. On the other hand, it is found that the probability of travel movements did not change at all for the flu pandemic in 2009. The pandemic did not affect potential travelers despite the WHO alert.

Responding to Communicable Diseases in Internationally Mobile Populations at Points of Entry and along Porous Borders, Nigeria, Benin, and Togo

PubMed Central

Rogers, Kimberly; Ward, Sarah; Ojo, Olubumni; Kakaī, Clement Glele; Agbeko, Tamekloe Tsidi; Garba, Hassan; MacGurn, Amanda; Oppert, Marydale; Kone, Idrissa; Bamsa, Olutola; Schneider, Dana; Brown, Clive

2017-01-01

Recent multinational disease outbreaks demonstrate the risk of disease spreading globally before public health systems can respond to an event. To ensure global health security, countries need robust multisectoral systems to rapidly detect and respond to domestic or imported communicable diseases. The US Centers for Disease Control and Prevention International Border Team works with the governments of Nigeria, Togo, and Benin, along with Pro-Health International and the Abidjan-Lagos Corridor Organization, to build sustainable International Health Regulations capacities at points of entry (POEs) and along border regions. Together, we strengthen comprehensive national and regional border health systems by developing public health emergency response plans for POEs, conducting qualitative assessments of public health preparedness and response capacities at ground crossings, integrating internationally mobile populations into national health surveillance systems, and formalizing cross-border public health coordination. Achieving comprehensive national and regional border health capacity, which advances overall global health security, necessitates multisectoral dedication to the aforementioned components. PMID:29155668

Responding to Communicable Diseases in Internationally Mobile Populations at Points of Entry and along Porous Borders, Nigeria, Benin, and Togo.

PubMed

Merrill, Rebecca D; Rogers, Kimberly; Ward, Sarah; Ojo, Olubumni; Kakaī, Clement Glele; Agbeko, Tamekloe Tsidi; Garba, Hassan; MacGurn, Amanda; Oppert, Marydale; Kone, Idrissa; Bamsa, Olutola; Schneider, Dana; Brown, Clive

2017-12-01

Recent multinational disease outbreaks demonstrate the risk of disease spreading globally before public health systems can respond to an event. To ensure global health security, countries need robust multisectoral systems to rapidly detect and respond to domestic or imported communicable diseases. The US Centers for Disease Control and Prevention International Border Team works with the governments of Nigeria, Togo, and Benin, along with Pro-Health International and the Abidjan-Lagos Corridor Organization, to build sustainable International Health Regulations capacities at points of entry (POEs) and along border regions. Together, we strengthen comprehensive national and regional border health systems by developing public health emergency response plans for POEs, conducting qualitative assessments of public health preparedness and response capacities at ground crossings, integrating internationally mobile populations into national health surveillance systems, and formalizing cross-border public health coordination. Achieving comprehensive national and regional border health capacity, which advances overall global health security, necessitates multisectoral dedication to the aforementioned components.

[Automated analyzer of enzyme immunoassay].

PubMed

Osawa, S

1995-09-01

Automated analyzers for enzyme immunoassay can be classified by several points of view: the kind of labeled antibodies or enzymes, detection methods, the number of tests per unit time, analytical time and speed per run. In practice, it is important for us consider the several points such as detection limits, the number of tests per unit time, analytical range, and precision. Most of the automated analyzers on the market can randomly access and measure samples. I will describe the recent advance of automated analyzers reviewing their labeling antibodies and enzymes, the detection methods, the number of test per unit time and analytical time and speed per test.

Early detection of health and welfare compromises through automated detection of behavioural changes in pigs.

PubMed

Matthews, Stephen G; Miller, Amy L; Clapp, James; Plötz, Thomas; Kyriazakis, Ilias

2016-11-01

Early detection of health and welfare compromises in commercial piggeries is essential for timely intervention to enhance treatment success, reduce impact on welfare, and promote sustainable pig production. Behavioural changes that precede or accompany subclinical and clinical signs may have diagnostic value. Often referred to as sickness behaviour, this encompasses changes in feeding, drinking, and elimination behaviours, social behaviours, and locomotion and posture. Such subtle changes in behaviour are not easy to quantify and require lengthy observation input by staff, which is impractical on a commercial scale. Automated early-warning systems may provide an alternative by objectively measuring behaviour with sensors to automatically monitor and detect behavioural changes. This paper aims to: (1) review the quantifiable changes in behaviours with potential diagnostic value; (2) subsequently identify available sensors for measuring behaviours; and (3) describe the progress towards automating monitoring and detection, which may allow such behavioural changes to be captured, measured, and interpreted and thus lead to automation in commercial, housed piggeries. Multiple sensor modalities are available for automatic measurement and monitoring of behaviour, which require humans to actively identify behavioural changes. This has been demonstrated for the detection of small deviations in diurnal drinking, deviations in feeding behaviour, monitoring coughs and vocalisation, and monitoring thermal comfort, but not social behaviour. However, current progress is in the early stages of developing fully automated detection systems that do not require humans to identify behavioural changes; e.g., through automated alerts sent to mobile phones. Challenges for achieving automation are multifaceted and trade-offs are considered between health, welfare, and costs, between analysis of individuals and groups, and between generic and compromise-specific behaviours. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Effects of Automation Types on Air Traffic Controller Situation Awareness and Performance

NASA Technical Reports Server (NTRS)

Sethumadhavan, A.

2009-01-01

The Joint Planning and Development Office has proposed the introduction of automated systems to help air traffic controllers handle the increasing volume of air traffic in the next two decades (JPDO, 2007). Because fully automated systems leave operators out of the decision-making loop (e.g., Billings, 1991), it is important to determine the right level and type of automation that will keep air traffic controllers in the loop. This study examined the differences in the situation awareness (SA) and collision detection performance of individuals when they worked with information acquisition, information analysis, decision and action selection and action implementation automation to control air traffic (Parasuraman, Sheridan, & Wickens, 2000). When the automation was unreliable, the time taken to detect an upcoming collision was significantly longer for all the automation types compared with the information acquisition automation. This poor performance following automation failure was mediated by SA, with lower SA yielding poor performance. Thus, the costs associated with automation failure are greater when automation is applied to higher order stages of information processing. Results have practical implications for automation design and development of SA training programs.

Eye blink detection for different driver states in conditionally automated driving and manual driving using EOG and a driver camera.

PubMed

Schmidt, Jürgen; Laarousi, Rihab; Stolzmann, Wolfgang; Karrer-Gauß, Katja

2018-06-01

In this article, we examine the performance of different eye blink detection algorithms under various constraints. The goal of the present study was to evaluate the performance of an electrooculogram- and camera-based blink detection process in both manually and conditionally automated driving phases. A further comparison between alert and drowsy drivers was performed in order to evaluate the impact of drowsiness on the performance of blink detection algorithms in both driving modes. Data snippets from 14 monotonous manually driven sessions (mean 2 h 46 min) and 16 monotonous conditionally automated driven sessions (mean 2 h 45 min) were used. In addition to comparing two data-sampling frequencies for the electrooculogram measures (50 vs. 25 Hz) and four different signal-processing algorithms for the camera videos, we compared the blink detection performance of 24 reference groups. The analysis of the videos was based on very detailed definitions of eyelid closure events. The correct detection rates for the alert and manual driving phases (maximum 94%) decreased significantly in the drowsy (minus 2% or more) and conditionally automated (minus 9% or more) phases. Blinking behavior is therefore significantly impacted by drowsiness as well as by automated driving, resulting in less accurate blink detection.

Automation of Classical QEEG Trending Methods for Early Detection of Delayed Cerebral Ischemia: More Work to Do.

PubMed

Wickering, Ellis; Gaspard, Nicolas; Zafar, Sahar; Moura, Valdery J; Biswal, Siddharth; Bechek, Sophia; OʼConnor, Kathryn; Rosenthal, Eric S; Westover, M Brandon

2016-06-01

The purpose of this study is to evaluate automated implementations of continuous EEG monitoring-based detection of delayed cerebral ischemia based on methods used in classical retrospective studies. We studied 95 patients with either Fisher 3 or Hunt Hess 4 to 5 aneurysmal subarachnoid hemorrhage who were admitted to the Neurosciences ICU and underwent continuous EEG monitoring. We implemented several variations of two classical algorithms for automated detection of delayed cerebral ischemia based on decreases in alpha-delta ratio and relative alpha variability. Of 95 patients, 43 (45%) developed delayed cerebral ischemia. Our automated implementation of the classical alpha-delta ratio-based trending method resulted in a sensitivity and specificity (Se,Sp) of (80,27)%, compared with the values of (100,76)% reported in the classic study using similar methods in a nonautomated fashion. Our automated implementation of the classical relative alpha variability-based trending method yielded (Se,Sp) values of (65,43)%, compared with (100,46)% reported in the classic study using nonautomated analysis. Our findings suggest that improved methods to detect decreases in alpha-delta ratio and relative alpha variability are needed before an automated EEG-based early delayed cerebral ischemia detection system is ready for clinical use.

Repeated Induction of Inattentional Blindness in a Simulated Aviation Environment

NASA Technical Reports Server (NTRS)

Kennedy, Kellie D.; Stephens, Chad L.; Williams, Ralph A.; Schutte, Paul C.

2017-01-01

The study reported herein is a subset of a larger investigation on the role of automation in the context of the flight deck and used a fixed-based, human-in-the-loop simulator. This paper explored the relationship between automation and inattentional blindness (IB) occurrences in a repeated induction paradigm using two types of runway incursions. The critical stimuli for both runway incursions were directly relevant to primary task performance. Sixty non-pilot participants performed the final five minutes of a landing scenario twice in one of three automation conditions: full automation (FA), partial automation (PA), and no automation (NA). The first induction resulted in a 70 percent (42 of 60) detection failure rate with those in the PA condition significantly more likely to detect the incursion compared to the FA condition or the NA condition. The second induction yielded a 50 percent detection failure rate. Although detection improved (detection failure rates declined) in all conditions, those in the FA condition demonstrated the greatest improvement with doubled detection rates. The detection behavior in the first trial did not preclude a failed detection in the second induction. Group membership (IB vs. Detection) in the FA condition showed a greater improvement than those in the NA condition and rated the Mental Demand and Effort subscales of the NASA-TLX (NASA Task Load Index) significantly higher for Time 2 compared Time 1. Participants in the FA condition used the experience of IB exposure to improve task performance whereas those in the NA condition did not, indicating the availability and reallocation of attentional resources in the FA condition. These findings support the role of engagement in operational attention detriment and the consideration of attentional failure causation to determine appropriate mitigation strategies.

Automated classification of mandibular cortical bone on dental panoramic radiographs for early detection of osteoporosis

NASA Astrophysics Data System (ADS)

Horiba, Kazuki; Muramatsu, Chisako; Hayashi, Tatsuro; Fukui, Tatsumasa; Hara, Takeshi; Katsumata, Akitoshi; Fujita, Hiroshi

2015-03-01

Findings on dental panoramic radiographs (DPRs) have shown that mandibular cortical index (MCI) based on the morphology of mandibular inferior cortex was significantly correlated with osteoporosis. MCI on DPRs can be categorized into one of three groups and has the high potential for identifying patients with osteoporosis. However, most DPRs are used only for diagnosing dental conditions by dentists in their routine clinical work. Moreover, MCI is not generally quantified but assessed subjectively. In this study, we investigated a computer-aided diagnosis (CAD) system that automatically classifies mandibular cortical bone for detection of osteoporotic patients at early stage. First, an inferior border of mandibular bone was detected by use of an active contour method. Second, regions of interest including the cortical bone are extracted and analyzed for its thickness and roughness. Finally, support vector machine (SVM) differentiate cases into three MCI categories by features including the thickness and roughness. Ninety eight DPRs were used to evaluate our proposed scheme. The number of cases classified to Class I, II, and III by a dental radiologist are 56, 25 and 17 cases, respectively. Experimental result based on the leave-one-out cross-validation evaluation showed that the sensitivities for the classes I, II, and III were 94.6%, 57.7% and 94.1%, respectively. Distribution of the groups in the feature space indicates a possibility of MCI quantification by the proposed method. Therefore, our scheme has a potential in identifying osteoporotic patients at an early stage.

Automated Corrosion Detection Program

DTIC Science & Technology

2001-10-01

More detailed explanations of the methodology development can be found in Hidden Corrosion Detection Technology Assessment, a paper presented at...Detection Program, a paper presented at the Fourth Joint DoD/FAA/NASA Conference on Aging Aircraft, 2000. AS&M PULSE. The PULSE system, developed...selection can be found in The Evaluation of Hidden Corrosion Detection Technologies on the Automated Corrosion Detection Program, a paper presented

An Automated Method for Landmark Identification and Finite-Element Modeling of the Lumbar Spine.

PubMed

Campbell, Julius Quinn; Petrella, Anthony J

2015-11-01

The purpose of this study was to develop a method for the automated creation of finite-element models of the lumbar spine. Custom scripts were written to extract bone landmarks of lumbar vertebrae and assemble L1-L5 finite-element models. End-plate borders, ligament attachment points, and facet surfaces were identified. Landmarks were identified to maintain mesh correspondence between meshes for later use in statistical shape modeling. 90 lumbar vertebrae were processed creating 18 subject-specific finite-element models. Finite-element model surfaces and ligament attachment points were reproduced within 1e-5 mm of the bone surface, including the critical contact surfaces of the facets. Element quality exceeded specifications in 97% of elements for the 18 models created. The current method is capable of producing subject-specific finite-element models of the lumbar spine with good accuracy, quality, and robustness. The automated methods developed represent advancement in the state of the art of subject-specific lumbar spine modeling to a scale not possible with prior manual and semiautomated methods.

DETECTION OF PUTATIVE ANTIMALARIAL-RESISTANT PLASMODIUM VIVAX IN ANOPHELES VECTORS AT THAILAND-CAMBODIA AND THAILAND-MYANMAR BORDERS.

PubMed

Rattaprasert, Pongruj; Chaksangchaichot, Panee; Wihokhoen, Benchawan; Suparach, Nutjaree; Sorosjinda-Nunthawarasilp, Prapa

2016-03-01

Monitoring of multidrug-resistant (MDR)falciparum and vivax malaria has recently been included in the Global Plan for Artemisinin Resistance Containment (GPARC) of the Greater Mekong Sub-region, particularly at the Thailand-Cambodia and Thailand-Myanmar borders. In parallel to GPARC, monitoring MDR malaria parasites in anopheline vectors is an ideal augment to entomological surveillance. Employing Plasmodium- and species-specific nested PCR techniques, only P. vivax was detected in 3/109 salivary gland DNA extracts of anopheline vectors collected during a rainy season between 24-26 August 2009 and 22-24 September 2009 and a dry season between 29-31 December 2009 and 16-18 January 2010. Indoor and out- door resting mosquitoes were collected in Thong Pha Phum District, Kanchanaburi Province (border of Thailand-Myanmar) and Bo Rai District, Trat Province (border of Thailand-Cambodia): one sample from Anopheles dirus at the Thailand-Cambodia border and two samples from An. aconitus from Thailand-Myanmar border isolate. Nucleotide sequencing of dihydrofolate reductase gene revealed the presence in all three samples of four mutations known to cause high resistance to antifolate pyrimethamine, but no mutations were found in multidrug resistance transporter 1 gene that are associated with (falciparum) resistance to quinoline antimalarials. Such findings indicate the potential usefulness of this approach in monitoring the prevalence of drug-resistant malaria parasites in geographically regions prone to the development of drug resistance and where screening of human population at risk poses logistical and ethical problems. Keywords: Anopheles spp, Plasmodium vivax, antimalarial resistance, Greater Mekong Sub-region, nested PCR, vector surveillance

Toward development of mobile application for hand arthritis screening.

PubMed

Akhbardeh, Farhad; Vasefi, Fartash; Tavakolian, Kouhyar; Bradley, David; Fazel-Rezai, Reza

2015-01-01

Arthritis is one of the most common health problems affecting people throughout the world. The goal of the work presented in this paper is to provide individuals, who may be developing or have developed arthritis, with a mobile application to assess and monitor the progress of their disease using their smartphone. The image processing algorithm includes finger border detection algorithm to monitor joint thickness and angular deviation abnormalities, which are common symptoms of arthritis. In this work, we have analyzed and compared gradient, thresholding and Canny algorithms for border detection. The effect of image spatial resolution (down-sampling) is also investigated. The results calculated based on 36 joint measurements show that the mean errors for gradient, thresholding, and Canny methods are 0.20, 2.13, and 2.03 mm, respectively. In addition, the average error for different image resolutions is analyzed and the minimum required resolution is determined for each method. The results confirm that recent smartphone imaging capabilities can provide enough accuracy for hand border detection and finger joint analysis based on gradient method.

Automated Content Detection for Cassini Images

NASA Astrophysics Data System (ADS)

Stanboli, A.; Bue, B.; Wagstaff, K.; Altinok, A.

2017-06-01

NASA missions generate numerous images ever organized in increasingly large archives. Image archives are currently not searchable by image content. We present an automated content detection prototype that can enable content search.

What Is an Automated External Defibrillator?

MedlinePlus

ANSWERS by heart Treatments + Tests What Is an Automated External Defibrillator? An automated external defibrillator (AED) is a lightweight, portable device ... ANSWERS by heart Treatments + Tests What Is an Automated External Defibrillator? detect a rhythm that should be ...

Rapid toxicity detection in water quality control utilizing automated multispecies biomonitoring for permanent space stations

NASA Technical Reports Server (NTRS)

Morgan, E. L.; Young, R. C.; Smith, M. D.; Eagleson, K. W.

1986-01-01

The objective of this study was to evaluate proposed design characteristics and applications of automated biomonitoring devices for real-time toxicity detection in water quality control on-board permanent space stations. Simulated tests in downlinking transmissions of automated biomonitoring data to Earth-receiving stations were simulated using satellite data transmissions from remote Earth-based stations.

Comparison of automated processing of flocked swabs with manual processing of fiber swabs for detection of nasal carriage of Staphylococcus aureus.

PubMed

Jones, Gillian; Matthews, Roger; Cunningham, Richard; Jenks, Peter

2011-07-01

The sensitivity of automated culture of Staphylococcus aureus from flocked swabs versus that of manual culture of fiber swabs was prospectively compared using nasal swabs from 867 patients. Automated culture from flocked swabs significantly increased the detection rate, by 13.1% for direct culture and 10.2% for enrichment culture.

An Automated Detection System for Microaneurysms That Is Effective across Different Racial Groups.

PubMed

Saleh, George Michael; Wawrzynski, James; Caputo, Silvestro; Peto, Tunde; Al Turk, Lutfiah Ismail; Wang, Su; Hu, Yin; Da Cruz, Lyndon; Smith, Phil; Tang, Hongying Lilian

2016-01-01

Patients without diabetic retinopathy (DR) represent a large proportion of the caseload seen by the DR screening service so reliable recognition of the absence of DR in digital fundus images (DFIs) is a prime focus of automated DR screening research. We investigate the use of a novel automated DR detection algorithm to assess retinal DFIs for absence of DR. A retrospective, masked, and controlled image-based study was undertaken. 17,850 DFIs of patients from six different countries were assessed for DR by the automated system and by human graders. The system's performance was compared across DFIs from the different countries/racial groups. The sensitivities for detection of DR by the automated system were Kenya 92.8%, Botswana 90.1%, Norway 93.5%, Mongolia 91.3%, China 91.9%, and UK 90.1%. The specificities were Kenya 82.7%, Botswana 83.2%, Norway 81.3%, Mongolia 82.5%, China 83.0%, and UK 79%. There was little variability in the calculated sensitivities and specificities across the six different countries involved in the study. These data suggest the possible scalability of an automated DR detection platform that enables rapid identification of patients without DR across a wide range of races.

Combining Image and Non-Image Data for Automatic Detection of Retina Disease in a Telemedicine Network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aykac, Deniz; Chaum, Edward; Fox, Karen

A telemedicine network with retina cameras and automated quality control, physiological feature location, and lesion/anomaly detection is a low-cost way of achieving broad-based screening for diabetic retinopathy (DR) and other eye diseases. In the process of a routine eye-screening examination, other non-image data is often available which may be useful in automated diagnosis of disease. In this work, we report on the results of combining this non-image data with image data, using the protocol and processing steps of a prototype system for automated disease diagnosis of retina examinations from a telemedicine network. The system includes quality assessments, automated physiology detection,more » and automated lesion detection to create an archive of known cases. Non-image data such as diabetes onset date and hemoglobin A1c (HgA1c) for each patient examination are included as well, and the system is used to create a content-based image retrieval engine capable of automated diagnosis of disease into 'normal' and 'abnormal' categories. The system achieves a sensitivity and specificity of 91.2% and 71.6% using hold-one-out validation testing.« less

The HTS barcode checker pipeline, a tool for automated detection of illegally traded species from high-throughput sequencing data.

PubMed

Lammers, Youri; Peelen, Tamara; Vos, Rutger A; Gravendeel, Barbara

2014-02-06

Mixtures of internationally traded organic substances can contain parts of species protected by the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). These mixtures often raise the suspicion of border control and customs offices, which can lead to confiscation, for example in the case of Traditional Chinese medicines (TCMs). High-throughput sequencing of DNA barcoding markers obtained from such samples provides insight into species constituents of mixtures, but manual cross-referencing of results against the CITES appendices is labor intensive. Matching DNA barcodes against NCBI GenBank using BLAST may yield misleading results both as false positives, due to incorrectly annotated sequences, and false negatives, due to spurious taxonomic re-assignment. Incongruence between the taxonomies of CITES and NCBI GenBank can result in erroneous estimates of illegal trade. The HTS barcode checker pipeline is an application for automated processing of sets of 'next generation' barcode sequences to determine whether these contain DNA barcodes obtained from species listed on the CITES appendices. This analytical pipeline builds upon and extends existing open-source applications for BLAST matching against the NCBI GenBank reference database and for taxonomic name reconciliation. In a single operation, reads are converted into taxonomic identifications matched with names on the CITES appendices. By inclusion of a blacklist and additional names databases, the HTS barcode checker pipeline prevents false positives and resolves taxonomic heterogeneity. The HTS barcode checker pipeline can detect and correctly identify DNA barcodes of CITES-protected species from reads obtained from TCM samples in just a few minutes. The pipeline facilitates and improves molecular monitoring of trade in endangered species, and can aid in safeguarding these species from extinction in the wild. The HTS barcode checker pipeline is available at https://github.com/naturalis/HTS-barcode-checker.

The HTS barcode checker pipeline, a tool for automated detection of illegally traded species from high-throughput sequencing data

PubMed Central

2014-01-01

Background Mixtures of internationally traded organic substances can contain parts of species protected by the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). These mixtures often raise the suspicion of border control and customs offices, which can lead to confiscation, for example in the case of Traditional Chinese medicines (TCMs). High-throughput sequencing of DNA barcoding markers obtained from such samples provides insight into species constituents of mixtures, but manual cross-referencing of results against the CITES appendices is labor intensive. Matching DNA barcodes against NCBI GenBank using BLAST may yield misleading results both as false positives, due to incorrectly annotated sequences, and false negatives, due to spurious taxonomic re-assignment. Incongruence between the taxonomies of CITES and NCBI GenBank can result in erroneous estimates of illegal trade. Results The HTS barcode checker pipeline is an application for automated processing of sets of 'next generation’ barcode sequences to determine whether these contain DNA barcodes obtained from species listed on the CITES appendices. This analytical pipeline builds upon and extends existing open-source applications for BLAST matching against the NCBI GenBank reference database and for taxonomic name reconciliation. In a single operation, reads are converted into taxonomic identifications matched with names on the CITES appendices. By inclusion of a blacklist and additional names databases, the HTS barcode checker pipeline prevents false positives and resolves taxonomic heterogeneity. Conclusions The HTS barcode checker pipeline can detect and correctly identify DNA barcodes of CITES-protected species from reads obtained from TCM samples in just a few minutes. The pipeline facilitates and improves molecular monitoring of trade in endangered species, and can aid in safeguarding these species from extinction in the wild. The HTS barcode checker pipeline is available at https://github.com/naturalis/HTS-barcode-checker. PMID:24502833

Automated detection of retinal disease.

PubMed

Helmchen, Lorens A; Lehmann, Harold P; Abràmoff, Michael D

2014-11-01

Nearly 4 in 10 Americans with diabetes currently fail to undergo recommended annual retinal exams, resulting in tens of thousands of cases of blindness that could have been prevented. Advances in automated retinal disease detection could greatly reduce the burden of labor-intensive dilated retinal examinations by ophthalmologists and optometrists and deliver diagnostic services at lower cost. As the current availability of ophthalmologists and optometrists is inadequate to screen all patients at risk every year, automated screening systems deployed in primary care settings and even in patients' homes could fill the current gap in supply. Expanding screens to all patients at risk by switching to automated detection systems would in turn yield significantly higher rates of detecting and treating diabetic retinopathy per dilated retinal examination. Fewer diabetic patients would develop complications such as blindness, while ophthalmologists could focus on more complex cases.

Automated detection of a prostate Ni-Ti stent in electronic portal images.

PubMed

Carl, Jesper; Nielsen, Henning; Nielsen, Jane; Lund, Bente; Larsen, Erik Hoejkjaer

2006-12-01

Planning target volumes (PTV) in fractionated radiotherapy still have to be outlined with wide margins to the clinical target volume due to uncertainties arising from daily shift of the prostate position. A recently proposed new method of visualization of the prostate is based on insertion of a thermo-expandable Ni-Ti stent. The current study proposes a new detection algorithm for automated detection of the Ni-Ti stent in electronic portal images. The algorithm is based on the Ni-Ti stent having a cylindrical shape with a fixed diameter, which was used as the basis for an automated detection algorithm. The automated method uses enhancement of lines combined with a grayscale morphology operation that looks for enhanced pixels separated with a distance similar to the diameter of the stent. The images in this study are all from prostate cancer patients treated with radiotherapy in a previous study. Images of a stent inserted in a humanoid phantom demonstrated a localization accuracy of 0.4-0.7 mm which equals the pixel size in the image. The automated detection of the stent was compared to manual detection in 71 pairs of orthogonal images taken in nine patients. The algorithm was successful in 67 of 71 pairs of images. The method is fast, has a high success rate, good accuracy, and has a potential for unsupervised localization of the prostate before radiotherapy, which would enable automated repositioning before treatment and allow for the use of very tight PTV margins.

Artemisinin resistance containment project in Thailand. (I): Implementation of electronic-based malaria information system for early case detection and individual case management in provinces along the Thai-Cambodian border.

PubMed

Khamsiriwatchara, Amnat; Sudathip, Prayuth; Sawang, Surasak; Vijakadge, Saowanit; Potithavoranan, Thanapon; Sangvichean, Aumnuyphan; Satimai, Wichai; Delacollette, Charles; Singhasivanon, Pratap; Lawpoolsri, Saranath; Kaewkungwal, Jaranit

2012-07-29

The Bureau of Vector-borne Diseases, Ministry of Public Health, Thailand, has implemented an electronic Malaria Information System (eMIS) as part of a strategy to contain artemisinin resistance. The attempt corresponds to the WHO initiative, funded by the Bill & Melinda Gates Foundation, to contain anti-malarial drug resistance in Southeast Asia. The main objective of this study was to demonstrate the eMIS' functionality and outputs after implementation for use in the Thailand artemisinin-resistance containment project. The eMIS had been functioning since 2009 in seven Thai-Cambodian border provinces. The eMIS has covered 61 malaria posts/clinics, 27 Vector-borne Disease Units covering 12,508 hamlets at risk of malaria infections. The eMIS was designed as an evidence-based and near real-time system to capture data for early case detection, intensive case investigation, monitoring drug compliance and on/off-site tracking of malarial patients, as well as collecting data indicating potential drug resistance among patients. Data captured by the eMIS in 2008-2011 were extracted and presented. The core functionalities of the eMIS have been utilized by malaria staff at all levels, from local operational units to ministerial management. The eMIS case detection module suggested decreasing trends during 2009-2011; the number of malaria cases detected in the project areas over the years studied were 3818, 2695, and 2566, with sero-positive rates of 1.24, 0.98, and 1.16%, respectively. The eMIS case investigation module revealed different trends in weekly Plasmodium falciparum case numbers, when classified by responsible operational unit, local and migrant status, and case-detection type. It was shown that most Thai patients were infected within their own residential district, while migrants were infected either at their working village or from across the border. The data mapped in the system suggested that P. falciparum-infected cases and potential drug-resistant cases were scattered mostly along the border villages. The mobile technology application has detected different follow-up rates, with particularly low rates among seasonal and cross-border migrants. The eMIS demonstrated that it could capture essential data from individual malaria cases at local operational units, while effectively being used for situation and trend analysis at upper-management levels. The system provides evidence-based information that could contribute to the control and containment of resistant parasites. Currently, the eMIS is expanding beyond the Thai-Cambodian project areas to the provinces that lie along the Thai-Myanmar border.

Automated detection of bacteria in urine

NASA Technical Reports Server (NTRS)

Fleig, A. J.; Picciolo, G. L.; Chappelle, E. W.; Kelbaugh, B. N.

1972-01-01

A method for detecting the presence of bacteria in urine was developed which utilizes the bioluminescent reaction of adenosine triphosphate with luciferin and luciferase derived from the tails of fireflies. The method was derived from work on extraterrestrial life detection. A device was developed which completely automates the assay process.

Border Lookout: Enhancing Tuberculosis Control on the United States-Mexico Border.

PubMed

DeSisto, Carla; Broussard, Kelly; Escobedo, Miguel; Borntrager, Denise; Alvarado-Ramy, Francisco; Waterman, Stephen

2015-10-01

We evaluated the use of federal public health intervention tools known as the Do Not Board and Border Lookout (BL) for detecting and referring infectious or potentially infectious land border travelers with tuberculosis (TB) back to treatment. We used data about the issuance of BL from April 2007 to September 2013 to examine demographics and TB laboratory results for persons on the list (N = 66) and time on the list before being located and achieving noninfectious status. The majority of case-patients were Hispanic and male, with a median age of 39 years. Most were citizens of the United States or Mexico, and 30.3% were undocumented migrants. One-fifth had multidrug-resistant TB. Nearly two-thirds of case-patients were located and treated as a result of being placed on the list. However, 25.8% of case-patients, primarily undocumented migrants, remain lost to follow-up and remain on the list. For this highly mobile patient population, the use of this novel federal travel intervention tool facilitated the detection and treatment of infectious TB cases that were lost to follow-up. © The American Society of Tropical Medicine and Hygiene.

Taiwan's Travel and Border Health Measures in Response to Zika.

PubMed

Ho, Li-Li; Tsai, Yu-Hui; Lee, Wang-Ping; Liao, Szu-Tsai; Wu, Li-Gin; Wu, Yi-Chun

Zika virus has recently emerged as a worldwide public health concern. Travel and border health measures stand as one of the main strategies and frontline defenses in responding to international epidemics. As of October 31, 2016, Taiwan has reported 13 imported cases, 5 of which were detected through routine entry screening and active monitoring at international airports. This article shares Taiwan's disease surveillance activities at designated points of entry and travel and border health measures in response to Zika. The Taiwan government collaborates with its tourism industry to disseminate information about precautionary measures and encourages tour guides to report suspected individuals or events to activate early response measures. Taiwan also engages in vector control activities at points of entry, including targeting aircraft from countries where vector-borne diseases are endemic, implementing mosquito sweep measures, and collecting vector surveillance data. In future emerging and reemerging disease events, entry surveillance at designated points of entry may enable early detection of diseases of international origin and more rapid activation of public health preparedness activities and international collaboration. Taiwan will continue to maximize border and travel health measures in compliance with IHR (2005) requirements, which rely on continued risk assessment, practical implementation activities, and engagement with all stakeholders.

Adverse drug events with hyperkalaemia during inpatient stays: evaluation of an automated method for retrospective detection in hospital databases

PubMed Central

2014-01-01

Background Adverse drug reactions and adverse drug events (ADEs) are major public health issues. Many different prospective tools for the automated detection of ADEs in hospital databases have been developed and evaluated. The objective of the present study was to evaluate an automated method for the retrospective detection of ADEs with hyperkalaemia during inpatient stays. Methods We used a set of complex detection rules to take account of the patient’s clinical and biological context and the chronological relationship between the causes and the expected outcome. The dataset consisted of 3,444 inpatient stays in a French general hospital. An automated review was performed for all data and the results were compared with those of an expert chart review. The complex detection rules’ analytical quality was evaluated for ADEs. Results In terms of recall, 89.5% of ADEs with hyperkalaemia “with or without an abnormal symptom” were automatically identified (including all three serious ADEs). In terms of precision, 63.7% of the automatically identified ADEs with hyperkalaemia were true ADEs. Conclusions The use of context-sensitive rules appears to improve the automated detection of ADEs with hyperkalaemia. This type of tool may have an important role in pharmacoepidemiology via the routine analysis of large inter-hospital databases. PMID:25212108

Adverse drug events with hyperkalaemia during inpatient stays: evaluation of an automated method for retrospective detection in hospital databases.

PubMed

Ficheur, Grégoire; Chazard, Emmanuel; Beuscart, Jean-Baptiste; Merlin, Béatrice; Luyckx, Michel; Beuscart, Régis

2014-09-12

Adverse drug reactions and adverse drug events (ADEs) are major public health issues. Many different prospective tools for the automated detection of ADEs in hospital databases have been developed and evaluated. The objective of the present study was to evaluate an automated method for the retrospective detection of ADEs with hyperkalaemia during inpatient stays. We used a set of complex detection rules to take account of the patient's clinical and biological context and the chronological relationship between the causes and the expected outcome. The dataset consisted of 3,444 inpatient stays in a French general hospital. An automated review was performed for all data and the results were compared with those of an expert chart review. The complex detection rules' analytical quality was evaluated for ADEs. In terms of recall, 89.5% of ADEs with hyperkalaemia "with or without an abnormal symptom" were automatically identified (including all three serious ADEs). In terms of precision, 63.7% of the automatically identified ADEs with hyperkalaemia were true ADEs. The use of context-sensitive rules appears to improve the automated detection of ADEs with hyperkalaemia. This type of tool may have an important role in pharmacoepidemiology via the routine analysis of large inter-hospital databases.

Effects of Response Bias and Judgment Framing on Operator Use of an Automated Aid in a Target Detection Task

ERIC Educational Resources Information Center

Rice, Stephen; McCarley, Jason S.

2011-01-01

Automated diagnostic aids prone to false alarms often produce poorer human performance in signal detection tasks than equally reliable miss-prone aids. However, it is not yet clear whether this is attributable to differences in the perceptual salience of the automated aids' misses and false alarms or is the result of inherent differences in…

Comparison of Automated Processing of Flocked Swabs with Manual Processing of Fiber Swabs for Detection of Nasal Carriage of Staphylococcus aureus▿‡

PubMed Central

Jones, Gillian; Matthews, Roger; Cunningham, Richard; Jenks, Peter

2011-01-01

The sensitivity of automated culture of Staphylococcus aureus from flocked swabs versus that of manual culture of fiber swabs was prospectively compared using nasal swabs from 867 patients. Automated culture from flocked swabs significantly increased the detection rate, by 13.1% for direct culture and 10.2% for enrichment culture. PMID:21525218

Comparison study of membrane filtration direct count and an automated coliform and Escherichia coli detection system for on-site water quality testing.

PubMed

Habash, Marc; Johns, Robert

2009-10-01

This study compared an automated Escherichia coli and coliform detection system with the membrane filtration direct count technique for water testing. The automated instrument performed equal to or better than the membrane filtration test in analyzing E. coli-spiked samples and blind samples with interference from Proteus vulgaris or Aeromonas hydrophila.

Using microwave Doppler radar in automated manufacturing applications

NASA Astrophysics Data System (ADS)

Smith, Gregory C.

Since the beginning of the Industrial Revolution, manufacturers worldwide have used automation to improve productivity, gain market share, and meet growing or changing consumer demand for manufactured products. To stimulate further industrial productivity, manufacturers need more advanced automation technologies: "smart" part handling systems, automated assembly machines, CNC machine tools, and industrial robots that use new sensor technologies, advanced control systems, and intelligent decision-making algorithms to "see," "hear," "feel," and "think" at the levels needed to handle complex manufacturing tasks without human intervention. The investigator's dissertation offers three methods that could help make "smart" CNC machine tools and industrial robots possible: (1) A method for detecting acoustic emission using a microwave Doppler radar detector, (2) A method for detecting tool wear on a CNC lathe using a Doppler radar detector, and (3) An online non-contact method for detecting industrial robot position errors using a microwave Doppler radar motion detector. The dissertation studies indicate that microwave Doppler radar could be quite useful in automated manufacturing applications. In particular, the methods developed may help solve two difficult problems that hinder further progress in automating manufacturing processes: (1) Automating metal-cutting operations on CNC machine tools by providing a reliable non-contact method for detecting tool wear, and (2) Fully automating robotic manufacturing tasks by providing a reliable low-cost non-contact method for detecting on-line position errors. In addition, the studies offer a general non-contact method for detecting acoustic emission that may be useful in many other manufacturing and non-manufacturing areas, as well (e.g., monitoring and nondestructively testing structures, materials, manufacturing processes, and devices). By advancing the state of the art in manufacturing automation, the studies may help stimulate future growth in industrial productivity, which also promises to fuel economic growth and promote economic stability. The study also benefits the Department of Industrial Technology at Iowa State University and the field of Industrial Technology by contributing to the ongoing "smart" machine research program within the Department of Industrial Technology and by stimulating research into new sensor technologies within the University and within the field of Industrial Technology.

Automated detection of diabetic retinopathy: barriers to translation into clinical practice.

PubMed

Abramoff, Michael D; Niemeijer, Meindert; Russell, Stephen R

2010-03-01

Automated identification of diabetic retinopathy (DR), the primary cause of blindness and visual loss for those aged 18-65 years, from color images of the retina has enormous potential to increase the quality, cost-effectiveness and accessibility of preventative care for people with diabetes. Through advanced image analysis techniques, retinal images are analyzed for abnormalities that define and correlate with the severity of DR. Translating automated DR detection into clinical practice will require surmounting scientific and nonscientific barriers. Scientific concerns, such as DR detection limits compared with human experts, can be studied and measured. Ethical, legal and political issues can be addressed, but are difficult or impossible to measure. The primary objective of this review is to survey the methods, potential benefits and limitations of automated detection in order to better manage translation into clinical practice, based on extensive experience with the systems we have developed.

Ventriculogram segmentation using boosted decision trees

NASA Astrophysics Data System (ADS)

McDonald, John A.; Sheehan, Florence H.

2004-05-01

Left ventricular status, reflected in ejection fraction or end systolic volume, is a powerful prognostic indicator in heart disease. Quantitative analysis of these and other parameters from ventriculograms (cine xrays of the left ventricle) is infrequently performed due to the labor required for manual segmentation. None of the many methods developed for automated segmentation has achieved clinical acceptance. We present a method for semi-automatic segmentation of ventriculograms based on a very accurate two-stage boosted decision-tree pixel classifier. The classifier determines which pixels are inside the ventricle at key ED (end-diastole) and ES (end-systole) frames. The test misclassification rate is about 1%. The classifier is semi-automatic, requiring a user to select 3 points in each frame: the endpoints of the aortic valve and the apex. The first classifier stage is 2 boosted decision-trees, trained using features such as gray-level statistics (e.g. median brightness) and image geometry (e.g. coordinates relative to user supplied 3 points). Second stage classifiers are trained using the same features as the first, plus the output of the first stage. Border pixels are determined from the segmented images using dilation and erosion. A curve is then fit to the border pixels, minimizing a penalty function that trades off fidelity to the border pixels with smoothness. ED and ES volumes, and ejection fraction are estimated from border curves using standard area-length formulas. On independent test data, the differences between automatic and manual volumes (and ejection fractions) are similar in size to the differences between two human observers.

Data for automated, high-throughput microscopy analysis of intracellular bacterial colonies using spot detection.

PubMed

Ernstsen, Christina L; Login, Frédéric H; Jensen, Helene H; Nørregaard, Rikke; Møller-Jensen, Jakob; Nejsum, Lene N

2017-10-01

Quantification of intracellular bacterial colonies is useful in strategies directed against bacterial attachment, subsequent cellular invasion and intracellular proliferation. An automated, high-throughput microscopy-method was established to quantify the number and size of intracellular bacterial colonies in infected host cells (Detection and quantification of intracellular bacterial colonies by automated, high-throughput microscopy, Ernstsen et al., 2017 [1]). The infected cells were imaged with a 10× objective and number of intracellular bacterial colonies, their size distribution and the number of cell nuclei were automatically quantified using a spot detection-tool. The spot detection-output was exported to Excel, where data analysis was performed. In this article, micrographs and spot detection data are made available to facilitate implementation of the method.

Food Safety Hazards and Microbiological Zoonoses in European Meat Imports Detected in Border Inspection in the Period 2008-2013.

PubMed

Jansen, W; Grabowski, N; Gerulat, B; Klein, G

2016-02-01

Microbiological contaminations and other food safety hazards are omnipresent within the European Union (EU) and a considerable risk for consumers, particularly in imported meat and meat products. The number of rejections at external EU borders has been increasing in recent years. Official authorities in each member state are therefore obliged to notify border rejections of food and animal feed due to a direct or indirect risk to human or animal health. This study explored the trends and temporal and spatial distribution of notifications on food safety hazards between January 2008 and December 2013 with a special emphasis on microbiological zoonoses in meat and meat products including poultry at border checks resulting from the rapid alert system for food and feed (RASFF). Results indicated that border rejection notifications are increasing exponentially, frequently due to Salmonella in poultry and shiga-toxin-producing E. coli in meat and meat products. © 2015 Blackwell Verlag GmbH.

[Establishment of Automation System for Detection of Alcohol in Blood].

PubMed

Tian, L L; Shen, Lei; Xue, J F; Liu, M M; Liang, L J

2017-02-01

To establish an automation system for detection of alcohol content in blood. The determination was performed by automated workstation of extraction-headspace gas chromatography （HS-GC）. The blood collection with negative pressure, sealing time of headspace bottle and sample needle were checked and optimized in the abstraction of automation system. The automatic sampling was compared with the manual sampling. The quantitative data obtained by the automated workstation of extraction-HS-GC for alcohol was stable. The relative differences of two parallel samples were less than 5%. The automated extraction was superior to the manual extraction. A good linear relationship was obtained at the alcohol concentration range of 0.1-3.0 mg/mL （ r ≥0.999） with good repeatability. The method is simple and quick, with more standard experiment process and accurate experimental data. It eliminates the error from the experimenter and has good repeatability, which can be applied to the qualitative and quantitative detections of alcohol in blood. Copyright© by the Editorial Department of Journal of Forensic Medicine

Automated Historical and Real-Time Cyclone Discovery With Multimodal Remote Satellite Measurements

NASA Astrophysics Data System (ADS)

Ho, S.; Talukder, A.; Liu, T.; Tang, W.; Bingham, A.

2008-12-01

Existing cyclone detection and tracking solutions involve extensive manual analysis of modeled-data and field campaign data by teams of experts. We have developed a novel automated global cyclone detection and tracking system by assimilating and sharing information from multiple remote satellites. This unprecedented solution of combining multiple remote satellite measurements in an autonomous manner allows leveraging off the strengths of each individual satellite. Use of multiple satellite data sources also results in significantly improved temporal tracking accuracy for cyclones. Our solution involves an automated feature extraction and machine learning technique based on an ensemble classifier and Kalman filter for cyclone detection and tracking from multiple heterogeneous satellite data sources. Our feature-based methodology that focuses on automated cyclone discovery is fundamentally different from, and actually complements, the well-known Dvorak technique for cyclone intensity estimation (that often relies on manual detection of cyclonic regions) from field and remote data. Our solution currently employs the QuikSCAT wind measurement and the merged level 3 TRMM precipitation data for automated cyclone discovery. Assimilation of other types of remote measurements is ongoing and planned in the near future. Experimental results of our automated solution on historical cyclone datasets demonstrate the superior performance of our automated approach compared to previous work. Performance of our detection solution compares favorably against the list of cyclones occurring in North Atlantic Ocean for the 2005 calendar year reported by the National Hurricane Center (NHC) in our initial analysis. We have also demonstrated the robustness of our cyclone tracking methodology in other regions over the world by using multiple heterogeneous satellite data for detection and tracking of three arbitrary historical cyclones in other regions. Our cyclone detection and tracking methodology can be applied to (i) historical data to support Earth scientists in climate modeling, cyclonic-climate interactions, and obtain a better understanding of the cause and effects of cyclone (e.g. cyclo-genesis), and (ii) automatic cyclone discovery in near real-time using streaming satellite to support and improve the planning of global cyclone field campaigns. Additional satellite data from GOES and other orbiting satellites can be easily assimilated and integrated into our automated cyclone detection and tracking module to improve the temporal tracking accuracy of cyclones down to ½ hr and reduce the incidence of false alarms.

Anatomic viral detection is automated: the application of a robotic molecular pathology system for the detection of DNA viruses in anatomic pathology substrates, using immunocytochemical and nucleic acid hybridization techniques.

PubMed Central

Montone, K. T.; Brigati, D. J.; Budgeon, L. R.

1989-01-01

This paper presents the first automated system for simultaneously detecting human papilloma, herpes simplex, adenovirus, or cytomegalovirus viral antigens and gene sequences in standard formalin-fixed, paraffin-embedded tissue substrates and tissue culture. These viruses can be detected by colorimetric in situ nucleic acid hybridization, using biotinylated DNA probes, or by indirect immunoperoxidase techniques, using polyclonal or monoclonal antibodies, in a 2.0-hour assay performed at a single automated robotic workstation. Images FIG. 1 FIG. 4 FIG. 5 FIG. 6 FIG. 7 FIG. 8 FIG. 9 FIG. 10 FIG. 11 PMID:2773514

Three-phase general border detection method for dermoscopy images using non-uniform illumination correction.

PubMed

Norton, Kerri-Ann; Iyatomi, Hitoshi; Celebi, M Emre; Ishizaki, Sumiko; Sawada, Mizuki; Suzaki, Reiko; Kobayashi, Ken; Tanaka, Masaru; Ogawa, Koichi

2012-08-01

Computer-aided diagnosis of dermoscopy images has shown great promise in developing a quantitative, objective way of classifying skin lesions. An important step in the classification process is lesion segmentation. Many studies have been successful in segmenting melanocytic skin lesions (MSLs), but few have focused on non-melanocytic skin lesions (NoMSLs), as the wide variety of lesions makes accurate segmentation difficult. We developed an automatic segmentation program for detecting borders of skin lesions in dermoscopy images. The method consists of a pre-processing phase, general lesion segmentation phase, including illumination correction, and bright region segmentation phase. We tested our method on a set of 107 NoMSLs and a set of 319 MSLs. Our method achieved precision/recall scores of 84.5% and 88.5% for NoMSLs, and 93.9% and 93.8% for MSLs, in comparison with manual extractions from four or five dermatologists. The accuracy of our method was competitive or better than five recently published methods. Our new method is the first method for detecting borders of both non-melanocytic and melanocytic skin lesions. © 2011 John Wiley & Sons A/S.

Resolution of canine ocular thelaziosis in avermectin-sensitive Border Collies from Spain.

PubMed

Calero-Bernal, Rafael; Sánchez-Murillo, José Marín; Alarcón-Elbal, Pedro María; Sánchez-Moro, José; Latrofa, Maria Stefanía; Dantas-Torres, Filipe; Otranto, Domenico

2014-02-24

Ocular thelaziosis by Thelazia callipaeda is an emerging disease that affects primarily dogs, but also cats, foxes and other wild carnivores, as well as humans. Three clinical cases of unilateral conjunctivitis caused by Thelazia nematodes were detected in Border Collie, a dog breed intolerant to the macrocyclic lactones. Animals came from southwestern Spain, on the border with Portugal. Eight worms were collected and identified molecularly as T. callipaeda by amplification and sequencing of partial cytochrome c oxidase subunit 1 gene. Oral treatment with mebendazole 20mg/kg (Telmin(®)) was effective in curing the infection. Copyright © 2013 Elsevier B.V. All rights reserved.

The complete mitochondrial genome of the Border Collie dog.

PubMed

Wu, An-Quan; Zhang, Yong-Liang; Li, Li-Li; Chen, Long; Yang, Tong-Wen

2016-01-01

Border Collie dog is one of the famous breed of dog. In the present work we report the complete mitochondrial genome sequence of Border Collie dog for the first time. The total length of the mitogenome was 16,730 bp with the base composition of 31.6% for A, 28.7% for T, 25.5% for C, and 14.2% for G and an A-T (60.3%)-rich feature was detected. It harbored 13 protein-coding genes, two ribosomal RNA genes, 22 transfer RNA genes and one non-coding control region (D-loop region). The arrangement of all genes was identical to the typical mitochondrial genomes of dogs.

Operations management system advanced automation: Fault detection isolation and recovery prototyping

NASA Technical Reports Server (NTRS)

Hanson, Matt

1990-01-01

The purpose of this project is to address the global fault detection, isolation and recovery (FDIR) requirements for Operation's Management System (OMS) automation within the Space Station Freedom program. This shall be accomplished by developing a selected FDIR prototype for the Space Station Freedom distributed processing systems. The prototype shall be based on advanced automation methodologies in addition to traditional software methods to meet the requirements for automation. A secondary objective is to expand the scope of the prototyping to encompass multiple aspects of station-wide fault management (SWFM) as discussed in OMS requirements documentation.

[Examination of processed vegetable foods for the presence of common DNA sequences of genetically modified tomatoes].

PubMed

Kitagawa, Mamiko; Nakamura, Kosuke; Kondo, Kazunari; Ubukata, Shoji; Akiyama, Hiroshi

2014-01-01

The contamination of processed vegetable foods with genetically modified tomatoes was investigated by the use of qualitative PCR methods to detect the cauliflower mosaic virus 35S promoter (P35S) and the kanamycin resistance gene (NPTII). DNA fragments of P35S and NPTII were detected in vegetable juice samples, possibly due to contamination with the genomes of cauliflower mosaic virus infecting juice ingredients of Brassica species and soil bacteria, respectively. Therefore, to detect the transformation construct sequences of GM tomatoes, primer pairs were designed for qualitative PCR to specifically detect the border region between P35S and NPTII, and the border region between nopaline synthase gene promoter and NPTII. No amplification of the targeted sequences was observed using genomic DNA purified from the juice ingredients. The developed qualitative PCR method is considered to be a reliable tool to check contamination of products with GM tomatoes.

Automated circumferential construction of first-order aqueous humor outflow pathways using spectral-domain optical coherence tomography

NASA Astrophysics Data System (ADS)

Huang, Alex S.; Belghith, Akram; Dastiridou, Anna; Chopra, Vikas; Zangwill, Linda M.; Weinreb, Robert N.

2017-06-01

The purpose was to create a three-dimensional (3-D) model of circumferential aqueous humor outflow (AHO) in a living human eye with an automated detection algorithm for Schlemm's canal (SC) and first-order collector channels (CC) applied to spectral-domain optical coherence tomography (SD-OCT). Anterior segment SD-OCT scans from a subject were acquired circumferentially around the limbus. A Bayesian Ridge method was used to approximate the location of the SC on infrared confocal laser scanning ophthalmoscopic images with a cross multiplication tool developed to initiate SC/CC detection automated through a fuzzy hidden Markov Chain approach. Automatic segmentation of SC and initial CC's was manually confirmed by two masked graders. Outflow pathways detected by the segmentation algorithm were reconstructed into a 3-D representation of AHO. Overall, only <1% of images (5114 total B-scans) were ungradable. Automatic segmentation algorithm performed well with SC detection 98.3% of the time and <0.1% false positive detection compared to expert grader consensus. CC was detected 84.2% of the time with 1.4% false positive detection. 3-D representation of AHO pathways demonstrated variably thicker and thinner SC with some clear CC roots. Circumferential (360 deg), automated, and validated AHO detection of angle structures in the living human eye with reconstruction was possible.

Automated methods for multiplexed pathogen detection.

PubMed

Straub, Timothy M; Dockendorff, Brian P; Quiñonez-Díaz, Maria D; Valdez, Catherine O; Shutthanandan, Janani I; Tarasevich, Barbara J; Grate, Jay W; Bruckner-Lea, Cynthia J

2005-09-01

Detection of pathogenic microorganisms in environmental samples is a difficult process. Concentration of the organisms of interest also co-concentrates inhibitors of many end-point detection methods, notably, nucleic acid methods. In addition, sensitive, highly multiplexed pathogen detection continues to be problematic. The primary function of the BEADS (Biodetection Enabling Analyte Delivery System) platform is the automated concentration and purification of target analytes from interfering substances, often present in these samples, via a renewable surface column. In one version of BEADS, automated immunomagnetic separation (IMS) is used to separate cells from their samples. Captured cells are transferred to a flow-through thermal cycler where PCR, using labeled primers, is performed. PCR products are then detected by hybridization to a DNA suspension array. In another version of BEADS, cell lysis is performed, and community RNA is purified and directly labeled. Multiplexed detection is accomplished by direct hybridization of the RNA to a planar microarray. The integrated IMS/PCR version of BEADS can successfully purify and amplify 10 E. coli O157:H7 cells from river water samples. Multiplexed PCR assays for the simultaneous detection of E. coli O157:H7, Salmonella, and Shigella on bead suspension arrays was demonstrated for the detection of as few as 100 cells for each organism. Results for the RNA version of BEADS are also showing promising results. Automation yields highly purified RNA, suitable for multiplexed detection on microarrays, with microarray detection specificity equivalent to PCR. Both versions of the BEADS platform show great promise for automated pathogen detection from environmental samples. Highly multiplexed pathogen detection using PCR continues to be problematic, but may be required for trace detection in large volume samples. The RNA approach solves the issues of highly multiplexed PCR and provides "live vs. dead" capabilities. However, sensitivity of the method will need to be improved for RNA analysis to replace PCR.

Automated Methods for Multiplexed Pathogen Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Straub, Tim M.; Dockendorff, Brian P.; Quinonez-Diaz, Maria D.

2005-09-01

Detection of pathogenic microorganisms in environmental samples is a difficult process. Concentration of the organisms of interest also co-concentrates inhibitors of many end-point detection methods, notably, nucleic acid methods. In addition, sensitive, highly multiplexed pathogen detection continues to be problematic. The primary function of the BEADS (Biodetection Enabling Analyte Delivery System) platform is the automated concentration and purification of target analytes from interfering substances, often present in these samples, via a renewable surface column. In one version of BEADS, automated immunomagnetic separation (IMS) is used to separate cells from their samples. Captured cells are transferred to a flow-through thermal cyclermore » where PCR, using labeled primers, is performed. PCR products are then detected by hybridization to a DNA suspension array. In another version of BEADS, cell lysis is performed, and community RNA is purified and directly labeled. Multiplexed detection is accomplished by direct hybridization of the RNA to a planar microarray. The integrated IMS/PCR version of BEADS can successfully purify and amplify 10 E. coli O157:H7 cells from river water samples. Multiplexed PCR assays for the simultaneous detection of E. coli O157:H7, Salmonella, and Shigella on bead suspension arrays was demonstrated for the detection of as few as 100 cells for each organism. Results for the RNA version of BEADS are also showing promising results. Automation yields highly purified RNA, suitable for multiplexed detection on microarrays, with microarray detection specificity equivalent to PCR. Both versions of the BEADS platform show great promise for automated pathogen detection from environmental samples. Highly multiplexed pathogen detection using PCR continues to be problematic, but may be required for trace detection in large volume samples. The RNA approach solves the issues of highly multiplexed PCR and provides ''live vs. dead'' capabilities. However, sensitivity of the method will need to be improved for RNA analysis to replace PCR.« less

A novel tool for high-throughput screening of granulocyte-specific antibodies using the automated flow cytometric granulocyte immunofluorescence test (Flow-GIFT).

PubMed

Nguyen, Xuan Duc; Dengler, Thomas; Schulz-Linkholt, Monika; Klüter, Harald

2011-02-03

Transfusion-related acute lung injury (TRALI) is a severe complication related with blood transfusion. TRALI has usually been associated with antibodies against leukocytes. The flow cytometric granulocyte immunofluorescence test (Flow-GIFT) has been introduced for routine use when investigating patients and healthy blood donors. Here we describe a novel tool in the automation of the Flow-GIFT that enables a rapid screening of blood donations. We analyzed 440 sera from healthy female blood donors for the presence of granulocyte antibodies. As positive controls, 12 sera with known antibodies against anti-HNA-1a, -b, -2a; and -3a were additionally investigated. Whole-blood samples from HNA-typed donors were collected and the test cells isolated using cell sedimentation in a Ficoll density gradient. Subsequently, leukocytes were incubated with the respective serum and binding of antibodies was detected using FITC-conjugated antihuman antibody. 7-AAD was used to exclude dead cells. Pipetting steps were automated using the Biomek NXp Multichannel Automation Workstation. All samples were prepared in the 96-deep well plates and analyzed by flow cytometry. The standard granulocyte immunofluorescence test (GIFT) and granulocyte agglutination test (GAT) were also performed as reference methods. Sixteen sera were positive in the automated Flow-GIFT, while five of these sera were negative in the standard GIFT (anti-HNA 3a, n = 3; anti-HNA-1b, n = 1) and GAT (anti-HNA-2a, n = 1). The automated Flow-GIFT was able to detect all granulocyte antibodies, which could be only detected in GIFT in combination with GAT. In serial dilution tests, the automated Flow-GIFT detected the antibodies at higher dilutions than the reference methods GIFT and GAT. The Flow-GIFT proved to be feasible for automation. This novel high-throughput system allows an effective antigranulocyte antibody detection in a large donor population in order to prevent TRALI due to transfusion of blood products.

First multiphoton tomography of brain in man

NASA Astrophysics Data System (ADS)

König, Karsten; Kantelhardt, Sven R.; Kalasauskas, Darius; Kim, Ella; Giese, Alf

2016-03-01

We report on the first two-photon in vivo brain tissue imaging study in man. High resolution in vivo histology by multiphoton tomography (MPT) including two-photon FLIM was performed in the operation theatre during neurosurgery to evaluate the feasibility to detect label-free tumor borders with subcellular resolution. This feasibility study demonstrates, that MPT has the potential to identify tumor borders on a cellular level in nearly real-time.

Statistical image segmentation for the detection of skin lesion borders in UV fluorescence excitation

NASA Astrophysics Data System (ADS)

Ortega-Martinez, Antonio; Padilla-Martinez, Juan Pablo; Franco, Walfre

2016-04-01

The skin contains several fluorescent molecules or fluorophores that serve as markers of structure, function and composition. UV fluorescence excitation photography is a simple and effective way to image specific intrinsic fluorophores, such as the one ascribed to tryptophan which emits at a wavelength of 345 nm upon excitation at 295 nm, and is a marker of cellular proliferation. Earlier, we built a clinical UV photography system to image cellular proliferation. In some samples, the naturally low intensity of the fluorescence can make it difficult to separate the fluorescence of cells in higher proliferation states from background fluorescence and other imaging artifacts -- like electronic noise. In this work, we describe a statistical image segmentation method to separate the fluorescence of interest. Statistical image segmentation is based on image averaging, background subtraction and pixel statistics. This method allows to better quantify the intensity and surface distributions of fluorescence, which in turn simplify the detection of borders. Using this method we delineated the borders of highly-proliferative skin conditions and diseases, in particular, allergic contact dermatitis, psoriatic lesions and basal cell carcinoma. Segmented images clearly define lesion borders. UV fluorescence excitation photography along with statistical image segmentation may serve as a quick and simple diagnostic tool for clinicians.

Restoration of Motion-Blurred Image Based on Border Deformation Detection: A Traffic Sign Restoration Model

PubMed Central

Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Wang, Qi; Gao, Jing

2015-01-01

Due to the rapid development of motor vehicle Driver Assistance Systems (DAS), the safety problems associated with automatic driving have become a hot issue in Intelligent Transportation. The traffic sign is one of the most important tools used to reinforce traffic rules. However, traffic sign image degradation based on computer vision is unavoidable during the vehicle movement process. In order to quickly and accurately recognize traffic signs in motion-blurred images in DAS, a new image restoration algorithm based on border deformation detection in the spatial domain is proposed in this paper. The border of a traffic sign is extracted using color information, and then the width of the border is measured in all directions. According to the width measured and the corresponding direction, both the motion direction and scale of the image can be confirmed, and this information can be used to restore the motion-blurred image. Finally, a gray mean grads (GMG) ratio is presented to evaluate the image restoration quality. Compared to the traditional restoration approach which is based on the blind deconvolution method and Lucy-Richardson method, our method can greatly restore motion blurred images and improve the correct recognition rate. Our experiments show that the proposed method is able to restore traffic sign information accurately and efficiently. PMID:25849350

Restoration of motion-blurred image based on border deformation detection: a traffic sign restoration model.

PubMed

Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Wang, Qi; Gao, Jing

2015-01-01

Due to the rapid development of motor vehicle Driver Assistance Systems (DAS), the safety problems associated with automatic driving have become a hot issue in Intelligent Transportation. The traffic sign is one of the most important tools used to reinforce traffic rules. However, traffic sign image degradation based on computer vision is unavoidable during the vehicle movement process. In order to quickly and accurately recognize traffic signs in motion-blurred images in DAS, a new image restoration algorithm based on border deformation detection in the spatial domain is proposed in this paper. The border of a traffic sign is extracted using color information, and then the width of the border is measured in all directions. According to the width measured and the corresponding direction, both the motion direction and scale of the image can be confirmed, and this information can be used to restore the motion-blurred image. Finally, a gray mean grads (GMG) ratio is presented to evaluate the image restoration quality. Compared to the traditional restoration approach which is based on the blind deconvolution method and Lucy-Richardson method, our method can greatly restore motion blurred images and improve the correct recognition rate. Our experiments show that the proposed method is able to restore traffic sign information accurately and efficiently.

Taiwan's Travel and Border Health Measures in Response to Zika

PubMed Central

Ho, Li-Li; Tsai, Yu-Hui; Lee, Wang-Ping; Liao, Szu-Tsai; Wu, Li-Gin

2017-01-01

Zika virus has recently emerged as a worldwide public health concern. Travel and border health measures stand as one of the main strategies and frontline defenses in responding to international epidemics. As of October 31, 2016, Taiwan has reported 13 imported cases, 5 of which were detected through routine entry screening and active monitoring at international airports. This article shares Taiwan's disease surveillance activities at designated points of entry and travel and border health measures in response to Zika. The Taiwan government collaborates with its tourism industry to disseminate information about precautionary measures and encourages tour guides to report suspected individuals or events to activate early response measures. Taiwan also engages in vector control activities at points of entry, including targeting aircraft from countries where vector-borne diseases are endemic, implementing mosquito sweep measures, and collecting vector surveillance data. In future emerging and reemerging disease events, entry surveillance at designated points of entry may enable early detection of diseases of international origin and more rapid activation of public health preparedness activities and international collaboration. Taiwan will continue to maximize border and travel health measures in compliance with IHR (2005) requirements, which rely on continued risk assessment, practical implementation activities, and engagement with all stakeholders. PMID:28418744

Assessment of the repeatability and border-plate effects of the B158/B60 enzyme-linked-immunosorbent assay for the detection of circulating antigens (Ag-ELISA) of Taenia saginata.

PubMed

Jansen, Famke; Dorny, Pierre; Berkvens, Dirk; Van Hul, Anke; Van den Broeck, Nick; Makay, Caroline; Praet, Nicolas; Gabriël, Sarah

2016-08-30

The monoclonal antibody-based circulating antigen detecting ELISA (B158/B60 Ag-ELISA) has been used elaborately in several studies for the diagnosis of human, bovine and porcine cysticercosis. Interpretation of test results requires a good knowledge of the test characteristics, including the repeatability and the effect of the borders of the ELISA plates. Repeatability was tested for 4 antigen-negative and 5 antigen-positive reference bovine serum samples by calculating the Percentage Coefficient of Variation (%CV) within and between plates, within and between runs, overall, for two batches of monoclonal antibodies and by 2 laboratory technicians. All CV values obtained were below 20% (except one: 24.45%), which indicates a good repeatability and a negligible technician error. The value of 24.45% for indicating the variability between batches of monoclonal antibodies for one positive sample is still acceptable for repeatability measures. Border effects were determined by calculating the %CV values between the inner and outer wells of one plate for 2 positive serum samples. Variability is a little more present in the outer wells but this effect is very small and no significant border effect was found. Copyright © 2016 Elsevier B.V. All rights reserved.

Dental non-linear image registration and collection method with 3D reconstruction and change detection

NASA Astrophysics Data System (ADS)

Rahmes, Mark; Fagan, Dean; Lemieux, George

2017-03-01

The capability of a software algorithm to automatically align same-patient dental bitewing and panoramic x-rays over time is complicated by differences in collection perspectives. We successfully used image correlation with an affine transform for each pixel to discover common image borders, followed by a non-linear homography perspective adjustment to closely align the images. However, significant improvements in image registration could be realized if images were collected from the same perspective, thus facilitating change analysis. The perspective differences due to current dental image collection devices are so significant that straightforward change analysis is not possible. To address this, a new custom dental tray could be used to provide the standard reference needed for consistent positioning of a patient's mouth. Similar to sports mouth guards, the dental tray could be fabricated in standard sizes from plastic and use integrated electronics that have been miniaturized. In addition, the x-ray source needs to be consistently positioned in order to collect images with similar angles and scales. Solving this pose correction is similar to solving for collection angle in aerial imagery for change detection. A standard collection system would provide a method for consistent source positioning using real-time sensor position feedback from a digital x-ray image reference. Automated, robotic sensor positioning could replace manual adjustments. Given an image set from a standard collection, a disparity map between images can be created using parallax from overlapping viewpoints to enable change detection. This perspective data can be rectified and used to create a three-dimensional dental model reconstruction.

Voxel-based morphometry and automated lobar volumetry: The trade-off between spatial scale and statistical correction

PubMed Central

Voormolen, Eduard H.J.; Wei, Corie; Chow, Eva W.C.; Bassett, Anne S.; Mikulis, David J.; Crawley, Adrian P.

2011-01-01

Voxel-based morphometry (VBM) and automated lobar region of interest (ROI) volumetry are comprehensive and fast methods to detect differences in overall brain anatomy on magnetic resonance images. However, VBM and automated lobar ROI volumetry have detected dissimilar gray matter differences within identical image sets in our own experience and in previous reports. To gain more insight into how diverging results arise and to attempt to establish whether one method is superior to the other, we investigated how differences in spatial scale and in the need to statistically correct for multiple spatial comparisons influence the relative sensitivity of either technique to group differences in gray matter volumes. We assessed the performance of both techniques on a small dataset containing simulated gray matter deficits and additionally on a dataset of 22q11-deletion syndrome patients with schizophrenia (22q11DS-SZ) vs. matched controls. VBM was more sensitive to simulated focal deficits compared to automated ROI volumetry, and could detect global cortical deficits equally well. Moreover, theoretical calculations of VBM and ROI detection sensitivities to focal deficits showed that at increasing ROI size, ROI volumetry suffers more from loss in sensitivity than VBM. Furthermore, VBM and automated ROI found corresponding GM deficits in 22q11DS-SZ patients, except in the parietal lobe. Here, automated lobar ROI volumetry found a significant deficit only after a smaller subregion of interest was employed. Thus, sensitivity to focal differences is impaired relatively more by averaging over larger volumes in automated ROI methods than by the correction for multiple comparisons in VBM. These findings indicate that VBM is to be preferred over automated lobar-scale ROI volumetry for assessing gray matter volume differences between groups. PMID:19619660

Border-oriented post-processing refinement on detected vehicle bounding box for ADAS

NASA Astrophysics Data System (ADS)

Chen, Xinyuan; Zhang, Zhaoning; Li, Minne; Li, Dongsheng

2018-04-01

We investigate a new approach for improving localization accuracy of detected vehicles for object detection in advanced driver assistance systems(ADAS). Specifically, we implement a bounding box refinement as a post-processing of the state-of-the-art object detectors (Faster R-CNN, YOLOv2, etc.). The bounding box refinement is achieved by individually adjusting each border of the detected bounding box to its target location using a regression method. We use HOG features which perform well on the edge detection of vehicles to train the regressor and the regressor is independent of the CNN-based object detectors. Experiment results on the KITTI 2012 benchmark show that we can achieve up to 6% improvements over YOLOv2 and Faster R-CNN object detectors on the IoU threshold of 0.8. Also, the proposed refinement framework is computationally light, allowing for processing one bounding box within a few milliseconds on CPU. Further, this refinement method can be added to any object detectors, especially those with high speed but less accuracy.

Economic effects of Ohio's smoke-free law on Kentucky and Ohio border counties.

PubMed

Pyles, Mark K; Hahn, Ellen J

2011-01-01

To determine if the Ohio statewide smoke-free law is associated with economic activity in Ohio or Kentucky counties that lie on the border between the two states. In November 2006, Ohio implemented a comprehensive statewide smoke-free law for all indoor workplaces. A feasible generalised least squares (FLGS) time series design to estimate the impact of the Ohio smoke-free law on Kentucky and Ohio border counties. Six Kentucky and six Ohio counties that lie on the border between the two states. All reporting hospitality and accommodation establishments in all Kentucky and Ohio counties including but not limited to food and drinking establishments, hotels and casinos. Total number of employees, total wages paid and number of reported establishments in all hospitality and accommodation services, 6 years before Ohio's law and 1 year after. There is no evidence of a disproportionate change in economic activity in Ohio or Kentucky border counties relative to their non-border counterparts. There was no evidence of a relation between Ohio's smoke-free law and economic activity in Kentucky border counties. The law generated a positive influence on wages and number of establishments in Ohio border counties. The null result cannot be explained by low test power, as minimum changes necessary in the dependent variables to detect a significant influence are very reasonable in size. Our data add to the large body of evidence that smoke-free laws are neutral with respect to the hospitality business across jurisdictions with and without laws.

Automated detection of diabetic retinopathy on digital fundus images.

PubMed

Sinthanayothin, C; Boyce, J F; Williamson, T H; Cook, H L; Mensah, E; Lal, S; Usher, D

2002-02-01

The aim was to develop an automated screening system to analyse digital colour retinal images for important features of non-proliferative diabetic retinopathy (NPDR). High performance pre-processing of the colour images was performed. Previously described automated image analysis systems were used to detect major landmarks of the retinal image (optic disc, blood vessels and fovea). Recursive region growing segmentation algorithms combined with the use of a new technique, termed a 'Moat Operator', were used to automatically detect features of NPDR. These features included haemorrhages and microaneurysms (HMA), which were treated as one group, and hard exudates as another group. Sensitivity and specificity data were calculated by comparison with an experienced fundoscopist. The algorithm for exudate recognition was applied to 30 retinal images of which 21 contained exudates and nine were without pathology. The sensitivity and specificity for exudate detection were 88.5% and 99.7%, respectively, when compared with the ophthalmologist. HMA were present in 14 retinal images. The algorithm achieved a sensitivity of 77.5% and specificity of 88.7% for detection of HMA. Fully automated computer algorithms were able to detect hard exudates and HMA. This paper presents encouraging results in automatic identification of important features of NPDR.

An Automated Energy Detection Algorithm Based on Morphological Filter Processing with a Semi-Disk Structure

DTIC Science & Technology

2018-01-01

statistical moments of order 2, 3, and 4. The probability density function (PDF) of the vibrational time series of a good bearing has a Gaussian...ARL-TR-8271 ● JAN 2018 US Army Research Laboratory An Automated Energy Detection Algorithm Based on Morphological Filter...when it is no longer needed. Do not return it to the originator. ARL-TR-8271 ● JAN 2018 US Army Research Laboratory An Automated

[Problems with placement and using of automated external defibrillators in Czech Republic].

PubMed

Olos, Tomás; Bursa, Filip; Gregor, Roman; Holes, David

2011-01-01

The use of automated external defibrillators improves the survival of adults who suffer from cardiopulmonary arrest. Automated external defibrillators detect ventricular fibrillation with almost perfect sensitivity and specificity. Authors describe the use of automated external defibrillator during cardiopulmonary resuscitation in a patient with sudden cardiac arrest during ice-hockey match. The article reports also the use of automated external defibrillators in children.

InPRO: Automated Indoor Construction Progress Monitoring Using Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Hamledari, Hesam

In this research, an envisioned automated intelligent robotic solution for automated indoor data collection and inspection that employs a series of unmanned aerial vehicles (UAV), entitled "InPRO", is presented. InPRO consists of four stages, namely: 1) automated path planning; 2) autonomous UAV-based indoor inspection; 3) automated computer vision-based assessment of progress; and, 4) automated updating of 4D building information models (BIM). The works presented in this thesis address the third stage of InPRO. A series of computer vision-based methods that automate the assessment of construction progress using images captured at indoor sites are introduced. The proposed methods employ computer vision and machine learning techniques to detect the components of under-construction indoor partitions. In particular, framing (studs), insulation, electrical outlets, and different states of drywall sheets (installing, plastering, and painting) are automatically detected using digital images. High accuracy rates, real-time performance, and operation without a priori information are indicators of the methods' promising performance.

Trace-Level Automated Mercury Speciation Analysis

PubMed Central

Taylor, Vivien F.; Carter, Annie; Davies, Colin; Jackson, Brian P.

2011-01-01

An automated system for methyl Hg analysis by purge and trap gas chromatography (GC) was evaluated, with comparison of several different instrument configurations including chromatography columns (packed column or capillary), detector (atomic fluorescence, AFS, or inductively coupled plasma mass spectrometry, ICP-MS, using quadrupole and sector field ICP- MS instruments). Method detection limits (MDL) of 0.042 pg and 0.030 pg for CH3Hg+ were achieved with the automated Hg analysis system configured with AFS and ICPMS detection, respectively. Capillary GC with temperature programming was effective in improving resolution and decreasing retention times of heavier Hg species (in this case C3H7Hg+) although carryover between samples was increased. With capillary GC, the MDL for CH3Hg+ was 0.25 pg for AFS detection and 0.060 pg for ICP-MS detection. The automated system was demonstrated to have high throughput (72 samples analyzed in 8 hours) requiring considerably less analyst time than the manual method for methyl mercury analysis described in EPA 1630. PMID:21572543

Automated detection of exudates for diabetic retinopathy screening

NASA Astrophysics Data System (ADS)

Fleming, Alan D.; Philip, Sam; Goatman, Keith A.; Williams, Graeme J.; Olson, John A.; Sharp, Peter F.

2007-12-01

Automated image analysis is being widely sought to reduce the workload required for grading images resulting from diabetic retinopathy screening programmes. The recognition of exudates in retinal images is an important goal for automated analysis since these are one of the indicators that the disease has progressed to a stage requiring referral to an ophthalmologist. Candidate exudates were detected using a multi-scale morphological process. Based on local properties, the likelihoods of a candidate being a member of classes exudate, drusen or background were determined. This leads to a likelihood of the image containing exudates which can be thresholded to create a binary decision. Compared to a clinical reference standard, images containing exudates were detected with sensitivity 95.0% and specificity 84.6% in a test set of 13 219 images of which 300 contained exudates. Depending on requirements, this method could form part of an automated system to detect images showing either any diabetic retinopathy or referable diabetic retinopathy.

Towards an Automated Acoustic Detection System for Free Ranging Elephants.

PubMed

Zeppelzauer, Matthias; Hensman, Sean; Stoeger, Angela S

The human-elephant conflict is one of the most serious conservation problems in Asia and Africa today. The involuntary confrontation of humans and elephants claims the lives of many animals and humans every year. A promising approach to alleviate this conflict is the development of an acoustic early warning system. Such a system requires the robust automated detection of elephant vocalizations under unconstrained field conditions. Today, no system exists that fulfills these requirements. In this paper, we present a method for the automated detection of elephant vocalizations that is robust to the diverse noise sources present in the field. We evaluate the method on a dataset recorded under natural field conditions to simulate a real-world scenario. The proposed method outperformed existing approaches and robustly and accurately detected elephants. It thus can form the basis for a future automated early warning system for elephants. Furthermore, the method may be a useful tool for scientists in bioacoustics for the study of wildlife recordings.

Automatic segmentation and 3D reconstruction of intravascular ultrasound images for a fast preliminar evaluation of vessel pathologies.

PubMed

Sanz-Requena, Roberto; Moratal, David; García-Sánchez, Diego Ramón; Bodí, Vicente; Rieta, José Joaquín; Sanchis, Juan Manuel

2007-03-01

Intravascular ultrasound (IVUS) imaging is used along with X-ray coronary angiography to detect vessel pathologies. Manual analysis of IVUS images is slow and time-consuming and it is not feasible for clinical purposes. A semi-automated method is proposed to generate 3D reconstructions from IVUS video sequences, so that a fast diagnose can be easily done, quantifying plaque length and severity as well as plaque volume of the vessels under study. The methodology described in this work has four steps: a pre-processing of IVUS images, a segmentation of media-adventitia contour, a detection of intima and plaque and a 3D reconstruction of the vessel. Preprocessing is intended to remove noise from the images without blurring the edges. Segmentation of media-adventitia contour is achieved using active contours (snakes). In particular, we use the gradient vector flow (GVF) as external force for the snakes. The detection of lumen border is obtained taking into account gray-level information of the inner part of the previously detected contours. A knowledge-based approach is used to determine which level of gray corresponds statistically to the different regions of interest: intima, plaque and lumen. The catheter region is automatically discarded. An estimate of plaque type is also given. Finally, 3D reconstruction of all detected regions is made. The suitability of this methodology has been verified for the analysis and visualization of plaque length, stenosis severity, automatic detection of the most problematic regions, calculus of plaque volumes and a preliminary estimation of plaque type obtaining for automatic measures of lumen and vessel area an average error smaller than 1mm(2) (equivalent aproximately to 10% of the average measure), for calculus of plaque and lumen volume errors smaller than 0.5mm(3) (equivalent approximately to 20% of the average measure) and for plaque type estimates a mismatch of less than 8% in the analysed frames.

Automated Selection of Hotspots (ASH): enhanced automated segmentation and adaptive step finding for Ki67 hotspot detection in adrenal cortical cancer.

PubMed

Lu, Hao; Papathomas, Thomas G; van Zessen, David; Palli, Ivo; de Krijger, Ronald R; van der Spek, Peter J; Dinjens, Winand N M; Stubbs, Andrew P

2014-11-25

In prognosis and therapeutics of adrenal cortical carcinoma (ACC), the selection of the most active areas in proliferative rate (hotspots) within a slide and objective quantification of immunohistochemical Ki67 Labelling Index (LI) are of critical importance. In addition to intratumoral heterogeneity in proliferative rate i.e. levels of Ki67 expression within a given ACC, lack of uniformity and reproducibility in the method of quantification of Ki67 LI may confound an accurate assessment of Ki67 LI. We have implemented an open source toolset, Automated Selection of Hotspots (ASH), for automated hotspot detection and quantification of Ki67 LI. ASH utilizes NanoZoomer Digital Pathology Image (NDPI) splitter to convert the specific NDPI format digital slide scanned from the Hamamatsu instrument into a conventional tiff or jpeg format image for automated segmentation and adaptive step finding hotspots detection algorithm. Quantitative hotspot ranking is provided by the functionality from the open source application ImmunoRatio as part of the ASH protocol. The output is a ranked set of hotspots with concomitant quantitative values based on whole slide ranking. We have implemented an open source automated detection quantitative ranking of hotspots to support histopathologists in selecting the 'hottest' hotspot areas in adrenocortical carcinoma. To provide wider community easy access to ASH we implemented a Galaxy virtual machine (VM) of ASH which is available from http://bioinformatics.erasmusmc.nl/wiki/Automated_Selection_of_Hotspots . The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/13000_2014_216.

Autofocusing and Polar Body Detection in Automated Cell Manipulation.

PubMed

Wang, Zenan; Feng, Chen; Ang, Wei Tech; Tan, Steven Yih Min; Latt, Win Tun

2017-05-01

Autofocusing and feature detection are two essential processes for performing automated biological cell manipulation tasks. In this paper, we have introduced a technique capable of focusing on a holding pipette and a mammalian cell under a bright-field microscope automatically, and a technique that can detect and track the presence and orientation of the polar body of an oocyte that is rotated at the tip of a micropipette. Both algorithms were evaluated by using mouse oocytes. Experimental results show that both algorithms achieve very high success rates: 100% and 96%. As robust and accurate image processing methods, they can be widely applied to perform various automated biological cell manipulations.

Molecular inference of sources and spreading patterns of Plasmodium falciparum malaria parasites in internally displaced persons settlements in Myanmar-China border area.

PubMed

Lo, Eugenia; Zhou, Guofa; Oo, Winny; Lee, Ming-Chieh; Baum, Elisabeth; Felgner, Philip L; Yang, Zhaoqing; Cui, Liwang; Yan, Guiyun

2015-07-01

In Myanmar, civil unrest and establishment of internally displaced persons (IDP) settlement along the Myanmar-China border have impacted malaria transmission. The growing IDP populations raise deep concerns about health impact on local communities. Microsatellite markers were used to examine the source and spreading patterns of Plasmodium falciparum between IDP settlement and surrounding villages in Myanmar along the China border. Genotypic structure of P. falciparum was compared over the past three years from the same area and the demographic history was inferred to determine the source of recent infections. In addition, we examined if border migration is a factor of P. falciparum infections in China by determining gene flow patterns across borders. Compared to local community, the IDP samples showed a reduced and consistently lower genetic diversity over the past three years. A strong signature of genetic bottleneck was detected in the IDP samples. P. falciparum infections from the border regions in China were genetically similar to Myanmar and parasite gene flow was not constrained by geographical distance. Reduced genetic diversity of P. falciparum suggested intense malaria control within the IDP settlement. Human movement was a key factor to the spread of malaria both locally in Myanmar and across the international border. Copyright © 2015 Elsevier B.V. All rights reserved.

Cooperative Monitoring Center Occasional Paper/8: Cooperative Border Security for Jordan: Assessment and Options

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qojas, M.

1999-03-01

This document is an analysis of options for unilateral and cooperative action to improve the security of Jordan's borders. Sections describe the current political, economic, and social interactions along Jordan's borders. Next, the document discusses border security strategy for cooperation among neighboring countries and the adoption of confidence-building measures. A practical cooperative monitoring system would consist of hardware for early warning, command and control, communications, and transportation. Technical solutions can expand opportunities for the detection and identification of intruders. Sensors (such as seismic, break-wire, pressure-sensing, etc.) can warn border security forces of intrusion and contribute to the identification of themore » intrusion and help formulate the response. This document describes conceptual options for cooperation, offering three scenarios that relate to three hypothetical levels (low, medium, and high) of cooperation. Potential cooperative efforts under a low cooperation scenario could include information exchanges on military equipment and schedules to prevent misunderstandings and the establishment of protocols for handling emergency situations or unusual circumstances. Measures under a medium cooperation scenario could include establishing joint monitoring groups for better communications, with hot lines and scheduled meetings. The high cooperation scenario describes coordinated responses, joint border patrols, and sharing border intrusion information. Finally, the document lists recommendations for organizational, technical, and operational initiatives that could be applicable to the current situation.« less

Sediment connectivity at source-bordering aeolian dunefields along the Colorado River in the Grand Canyon, USA

NASA Astrophysics Data System (ADS)

Sankey, Joel; Kasprak, Alan; Caster, Joshua; East, Amy; Fairley, Helen

2017-04-01

Aeolian dunefields that are primarily built and maintained with river-derived sediment are found in many river valleys throughout the world and are impacted by changes in climate, land use, and river regulation. Quantifying the dynamic response of these aeolian dunefields to alterations in river flow is especially difficult given the highly correlated nature of the interacting geomorphic and sediment transport processes that drive their formation and maintenance. We characterize the effects of controlled river floods on changes in sediment connectivity at source-bordering aeolian dunefields in the Grand Canyon, USA. Controlled floods from the Glen Canyon Dam are used to build sandbars along the Colorado River in Grand Canyon which provide the main sediment source for aeolian dunefields. Aeolian dunefields are a primary resource of concern for land managers in the Grand Canyon because they often contain buried archaeological features. To characterize dunefield response to controlled floods, we use a novel, automated approach for the mechanistic segregation of geomorphic change to discern the geomorphic processes responsible for driving topographic change in very high resolution digital elevation models-of-difference (DODs) that span multiple, consecutive controlled river floods at source-bordering dunefields. We subsequently compare the results of mechanistic segregation with modelled estimates of aeolian dunefield evolution in order to understand how dunefields respond to contemporary, anthropogenically-driven variability in sediment supply and connectivity. These methods provide a rapid technique for sediment budgeting and enable the inference of spatial and temporal patterns in sediment flux between the fluvial and aeolian domains. We anticipate that this approach will be adaptable to other river valleys where the interactions of aeolian, fluvial, and hillslope processes drive sediment connectivity for the maintenance of source-bordering aeolian dunefields.

Radiation Control on Uzbekistan Borders - Results and Perspectives

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petrenko, Vitaliy; Yuldashev, Bekhzod; Ismailov, Ulughbek

2009-12-02

The measures and actions on prevention, detection and response to criminal or unauthorized acts involving radioactive materials in Uzbekistan are presented. In frames of program of radiation monitoring to prevent illicit trafficking of nuclear and radioactive materials main customs border checkpoints were equipped with commercial radiation portal monitors. Special radiation monitors elaborated and manufactured in INP AS RU are installed in INP(main gates, research reactor and laboratory building) to provide nuclear security of Institute facilities. The experience of Uzbekistan in establishing radiation monitoring systems on its borders, their operation and maintenance would be useful for realization of proposed plan ofmore » strengthening measures to prevent illicit trafficking in Republics of Central Asia region.« less

Automated detection of diabetic retinopathy lesions on ultrawidefield pseudocolour images.

PubMed

Wang, Kang; Jayadev, Chaitra; Nittala, Muneeswar G; Velaga, Swetha B; Ramachandra, Chaithanya A; Bhaskaranand, Malavika; Bhat, Sandeep; Solanki, Kaushal; Sadda, SriniVas R

2018-03-01

We examined the sensitivity and specificity of an automated algorithm for detecting referral-warranted diabetic retinopathy (DR) on Optos ultrawidefield (UWF) pseudocolour images. Patients with diabetes were recruited for UWF imaging. A total of 383 subjects (754 eyes) were enrolled. Nonproliferative DR graded to be moderate or higher on the 5-level International Clinical Diabetic Retinopathy (ICDR) severity scale was considered as grounds for referral. The software automatically detected DR lesions using the previously trained classifiers and classified each image in the test set as referral-warranted or not warranted. Sensitivity, specificity and the area under the receiver operating curve (AUROC) of the algorithm were computed. The automated algorithm achieved a 91.7%/90.3% sensitivity (95% CI 90.1-93.9/80.4-89.4) with a 50.0%/53.6% specificity (95% CI 31.7-72.8/36.5-71.4) for detecting referral-warranted retinopathy at the patient/eye levels, respectively; the AUROC was 0.873/0.851 (95% CI 0.819-0.922/0.804-0.894). Diabetic retinopathy (DR) lesions were detected from Optos pseudocolour UWF images using an automated algorithm. Images were classified as referral-warranted DR with a high degree of sensitivity and moderate specificity. Automated analysis of UWF images could be of value in DR screening programmes and could allow for more complete and accurate disease staging. © 2017 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

Automated Immunomagnetic Separation and Microarray Detection of E. coli O157:H7 from Poultry Carcass Rinse

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chandler, Darrell P.; Brown, Jeremy D.; Call, Douglas R.

2001-09-01

We describe the development and application of a novel electromagnetic flow cell and fluidics system for automated immunomagnetic separation of E. coli directly from unprocessed poultry carcass rinse, and the biochemical coupling of automated sample preparation with nucleic acid microarrays without cell growth. Highly porous nickel foam was used as a magnetic flux conductor. Up to 32% recovery efficiency of 'total' E. coli was achieved within the automated system with 6 sec contact times and 15 minute protocol (from sample injection through elution), statistically similar to cell recovery efficiencies in > 1 hour 'batch' captures. The electromagnet flow cell allowedmore » complete recovery of 2.8 mm particles directly from unprocessed poultry carcass rinse whereas the batch system did not. O157:H7 cells were reproducibly isolated directly from unprocessed poultry rinse with 39% recovery efficiency at 103 cells ml-1 inoculum. Direct plating of washed beads showed positive recovery of O 157:H7 directly from carcass rinse at an inoculum of 10 cells ml-1. Recovered beads were used for direct PCR amplification and microarray detection, with a process-level detection limit (automated cell concentration through microarray detection) of < 103 cells ml-1 carcass rinse. The fluidic system and analytical approach described here are generally applicable to most microbial detection problems and applications.« less

A gated LaBr3(Ce) detector for border protection applications

NASA Astrophysics Data System (ADS)

Etile, A.; Denis-Petit, D.; Gaudefroy, L.; Meot, V.; Roig, O.

2018-01-01

We report on the dedicated implementation of the blocking technique for a LaBr3(Ce) detector as well as associated electronics and data acquisition system for border protection applications. The detector is meant to perform delayed γ-ray spectroscopy of fission fragments produced via photofission induced by a high intensity pulsed photon beam. The gating technique avoids saturation of the detection chain during irradiation. The resulting setup allows us to successfully perform delayed γ-ray spectroscopy starting only 30 ns after the gating operation. The measured energy resolution ranges from 5% to 6.5% at 662 keV depending on the γ-ray detection time after the gating operation.

Failure of the MicroScan WalkAway System To Detect Heteroresistance to Carbapenems in a Patient with Enterobacter aerogenes Bacteremia▿

PubMed Central

Gordon, N. C.; Wareham, D. W.

2009-01-01

We report the failure of the automated MicroScan WalkAway system to detect carbapenem heteroresistance in Enterobacter aerogenes. Carbapenem resistance has become an increasing concern in recent years, and robust surveillance is required to prevent dissemination of resistant strains. Reliance on automated systems may delay the detection of emerging resistance. PMID:19641071

Automated circumferential construction of first-order aqueous humor outflow pathways using spectral-domain optical coherence tomography.

PubMed

Huang, Alex S; Belghith, Akram; Dastiridou, Anna; Chopra, Vikas; Zangwill, Linda M; Weinreb, Robert N

2017-06-01

The purpose was to create a three-dimensional (3-D) model of circumferential aqueous humor outflow (AHO) in a living human eye with an automated detection algorithm for Schlemm’s canal (SC) and first-order collector channels (CC) applied to spectral-domain optical coherence tomography (SD-OCT). Anterior segment SD-OCT scans from a subject were acquired circumferentially around the limbus. A Bayesian Ridge method was used to approximate the location of the SC on infrared confocal laser scanning ophthalmoscopic images with a cross multiplication tool developed to initiate SC/CC detection automated through a fuzzy hidden Markov Chain approach. Automatic segmentation of SC and initial CC’s was manually confirmed by two masked graders. Outflow pathways detected by the segmentation algorithm were reconstructed into a 3-D representation of AHO. Overall, only <1% of images (5114 total B-scans) were ungradable. Automatic segmentation algorithm performed well with SC detection 98.3% of the time and <0.1% false positive detection compared to expert grader consensus. CC was detected 84.2% of the time with 1.4% false positive detection. 3-D representation of AHO pathways demonstrated variably thicker and thinner SC with some clear CC roots. Circumferential (360 deg), automated, and validated AHO detection of angle structures in the living human eye with reconstruction was possible.

Optimizing a neural network for detection of moving vehicles in video

NASA Astrophysics Data System (ADS)

Fischer, Noëlle M.; Kruithof, Maarten C.; Bouma, Henri

2017-10-01

In the field of security and defense, it is extremely important to reliably detect moving objects, such as cars, ships, drones and missiles. Detection and analysis of moving objects in cameras near borders could be helpful to reduce illicit trading, drug trafficking, irregular border crossing, trafficking in human beings and smuggling. Many recent benchmarks have shown that convolutional neural networks are performing well in the detection of objects in images. Most deep-learning research effort focuses on classification or detection on single images. However, the detection of dynamic changes (e.g., moving objects, actions and events) in streaming video is extremely relevant for surveillance and forensic applications. In this paper, we combine an end-to-end feedforward neural network for static detection with a recurrent Long Short-Term Memory (LSTM) network for multi-frame analysis. We present a practical guide with special attention to the selection of the optimizer and batch size. The end-to-end network is able to localize and recognize the vehicles in video from traffic cameras. We show an efficient way to collect relevant in-domain data for training with minimal manual labor. Our results show that the combination with LSTM improves performance for the detection of moving vehicles.

Detection of anti-salmonella flgk antibodies in chickens by automated capillary immunoassay

USDA-ARS?s Scientific Manuscript database

Western blot is a very useful tool to identify specific protein, but is tedious, labor-intensive and time-consuming. An automated "Simple Western" assay has recently been developed that enables the protein separation, blotting and detection in an automatic manner. However, this technology has not ...

Automated Monitoring with a BSP Fault-Detection Test

NASA Technical Reports Server (NTRS)

Bickford, Randall L.; Herzog, James P.

2003-01-01

The figure schematically illustrates a method and procedure for automated monitoring of an asset, as well as a hardware- and-software system that implements the method and procedure. As used here, asset could signify an industrial process, power plant, medical instrument, aircraft, or any of a variety of other systems that generate electronic signals (e.g., sensor outputs). In automated monitoring, the signals are digitized and then processed in order to detect faults and otherwise monitor operational status and integrity of the monitored asset. The major distinguishing feature of the present method is that the fault-detection function is implemented by use of a Bayesian sequential probability (BSP) technique. This technique is superior to other techniques for automated monitoring because it affords sensitivity, not only to disturbances in the mean values, but also to very subtle changes in the statistical characteristics (variance, skewness, and bias) of the monitored signals.

Automated detection scheme of architectural distortion in mammograms using adaptive Gabor filter

NASA Astrophysics Data System (ADS)

Yoshikawa, Ruriha; Teramoto, Atsushi; Matsubara, Tomoko; Fujita, Hiroshi

2013-03-01

Breast cancer is a serious health concern for all women. Computer-aided detection for mammography has been used for detecting mass and micro-calcification. However, there are challenges regarding the automated detection of the architectural distortion about the sensitivity. In this study, we propose a novel automated method for detecting architectural distortion. Our method consists of the analysis of the mammary gland structure, detection of the distorted region, and reduction of false positive results. We developed the adaptive Gabor filter for analyzing the mammary gland structure that decides filter parameters depending on the thickness of the gland structure. As for post-processing, healthy mammary glands that run from the nipple to the chest wall are eliminated by angle analysis. Moreover, background mammary glands are removed based on the intensity output image obtained from adaptive Gabor filter. The distorted region of the mammary gland is then detected as an initial candidate using a concentration index followed by binarization and labeling. False positives in the initial candidate are eliminated using 23 types of characteristic features and a support vector machine. In the experiments, we compared the automated detection results with interpretations by a radiologist using 50 cases (200 images) from the Digital Database of Screening Mammography (DDSM). As a result, true positive rate was 82.72%, and the number of false positive per image was 1.39. There results indicate that the proposed method may be useful for detecting architectural distortion in mammograms.

Analysis of Pvama1 genes from China-Myanmar border reveals little regional genetic differentiation of Plasmodium vivax populations.

PubMed

Zhu, Xiaotong; Zhao, Pan; Wang, Si; Liu, Fei; Liu, Jun; Wang, Jian; Yang, Zhaoqing; Yan, Guiyun; Fan, Qi; Cao, Yaming; Cui, Liwang

2016-11-29

With the premise of diminishing parasite genetic diversity following the reduction of malaria incidence, the analysis of polymorphic antigenic markers may provide important information about the impact of malaria control on local parasite populations. Here we evaluated the genetic diversity of Plasmodium vivax apical membrane antigen 1 (Pvama1) gene in a parasite population from the China-Myanmar border and compared it with global P. vivax populations. We performed evolutionary analysis to examine the genetic diversity, natural selection, and population differentiation of 73 Pvama1 sequences acquired from the China-Myanmar border as well as 615 publically available Pvama1 sequences from seven global P. vivax populations. A total of 308 Pvama1 haplotypes were identified among the global P. vivax isolates. The overall nucleotide diversity of Pvama1 gene among the 73 China-Myanmar border parasite isolates was 0.008 with 41 haplotypes being identified (Hd = 0.958). Domain I (DI) harbored the majority (26/33) of the polymorphic sites. The McDonald Kreitman test showed a significant positive selection across the ectodomain and the DI of Pvama1. The fixation index (F ST ) estimation between the China-Myanmar border, Thailand (0.01) and Myanmar (0.10) showed only slight geographical genetic differentiation. Notably, the Sal-I haplotype was not detected in any of the analyzed global isolates, whereas the Belem strain was restricted to the Thai population. The detected mutations are mapped outside the overlapped region of the predicted B-cell epitopes and intrinsically unstructured/disordered regions. This study revealed high levels of genetic diversity of Pvama1 in the P. vivax parasite population from the China-Myanmar border with DI displaying stronger diversifying selection than other domains. There were low levels of population subdivision among parasite populations from the Greater Mekong Subregion.

Automated biosurveillance data from England and Wales, 1991-2011.

PubMed

Enki, Doyo G; Noufaily, Angela; Garthwaite, Paul H; Andrews, Nick J; Charlett, André; Lane, Chris; Farrington, C Paddy

2013-01-01

Outbreak detection systems for use with very large multiple surveillance databases must be suited both to the data available and to the requirements of full automation. To inform the development of more effective outbreak detection algorithms, we analyzed 20 years of data (1991-2011) from a large laboratory surveillance database used for outbreak detection in England and Wales. The data relate to 3,303 distinct types of infectious pathogens, with a frequency range spanning 6 orders of magnitude. Several hundred organism types were reported each week. We describe the diversity of seasonal patterns, trends, artifacts, and extra-Poisson variability to which an effective multiple laboratory-based outbreak detection system must adjust. We provide empirical information to guide the selection of simple statistical models for automated surveillance of multiple organisms, in the light of the key requirements of such outbreak detection systems, namely, robustness, flexibility, and sensitivity.

Automated Biosurveillance Data from England and Wales, 1991–2011

PubMed Central

Enki, Doyo G.; Noufaily, Angela; Garthwaite, Paul H.; Andrews, Nick J.; Charlett, André; Lane, Chris

2013-01-01

Outbreak detection systems for use with very large multiple surveillance databases must be suited both to the data available and to the requirements of full automation. To inform the development of more effective outbreak detection algorithms, we analyzed 20 years of data (1991–2011) from a large laboratory surveillance database used for outbreak detection in England and Wales. The data relate to 3,303 distinct types of infectious pathogens, with a frequency range spanning 6 orders of magnitude. Several hundred organism types were reported each week. We describe the diversity of seasonal patterns, trends, artifacts, and extra-Poisson variability to which an effective multiple laboratory-based outbreak detection system must adjust. We provide empirical information to guide the selection of simple statistical models for automated surveillance of multiple organisms, in the light of the key requirements of such outbreak detection systems, namely, robustness, flexibility, and sensitivity. PMID:23260848

Segmentation of 3D ultrasound computer tomography reflection images using edge detection and surface fitting

NASA Astrophysics Data System (ADS)

Hopp, T.; Zapf, M.; Ruiter, N. V.

2014-03-01

An essential processing step for comparison of Ultrasound Computer Tomography images to other modalities, as well as for the use in further image processing, is to segment the breast from the background. In this work we present a (semi-) automated 3D segmentation method which is based on the detection of the breast boundary in coronal slice images and a subsequent surface fitting. The method was evaluated using a software phantom and in-vivo data. The fully automatically processed phantom results showed that a segmentation of approx. 10% of the slices of a dataset is sufficient to recover the overall breast shape. Application to 16 in-vivo datasets was performed successfully using semi-automated processing, i.e. using a graphical user interface for manual corrections of the automated breast boundary detection. The processing time for the segmentation of an in-vivo dataset could be significantly reduced by a factor of four compared to a fully manual segmentation. Comparison to manually segmented images identified a smoother surface for the semi-automated segmentation with an average of 11% of differing voxels and an average surface deviation of 2mm. Limitations of the edge detection may be overcome by future updates of the KIT USCT system, allowing a fully-automated usage of our segmentation approach.

Automated exploitation of sky polarization imagery.

PubMed

Sadjadi, Firooz A; Chun, Cornell S L

2018-03-10

We propose an automated method for detecting neutral points in the sunlit sky. Until now, detecting these singularities has been done manually. Results are presented that document the application of this method on a limited number of polarimetric images of the sky captured with a camera and rotating polarizer. The results are significant because a method for automatically detecting the neutral points may aid in the determination of the solar position when the sun is obscured and may have applications in meteorology and pollution detection and characterization.

Automating quantum dot barcode assays using microfluidics and magnetism for the development of a point-of-care device.

PubMed

Gao, Yali; Lam, Albert W Y; Chan, Warren C W

2013-04-24

The impact of detecting multiple infectious diseases simultaneously at point-of-care with good sensitivity, specificity, and reproducibility would be enormous for containing the spread of diseases in both resource-limited and rich countries. Many barcoding technologies have been introduced for addressing this need as barcodes can be applied to detecting thousands of genetic and protein biomarkers simultaneously. However, the assay process is not automated and is tedious and requires skilled technicians. Barcoding technology is currently limited to use in resource-rich settings. Here we used magnetism and microfluidics technology to automate the multiple steps in a quantum dot barcode assay. The quantum dot-barcoded microbeads are sequentially (a) introduced into the chip, (b) magnetically moved to a stream containing target molecules, (c) moved back to the original stream containing secondary probes, (d) washed, and (e) finally aligned for detection. The assay requires 20 min, has a limit of detection of 1.2 nM, and can detect genetic targets for HIV, hepatitis B, and syphilis. This study provides a simple strategy to automate the entire barcode assay process and moves barcoding technologies one step closer to point-of-care applications.

Thermal infrared panoramic imaging sensor

NASA Astrophysics Data System (ADS)

Gutin, Mikhail; Tsui, Eddy K.; Gutin, Olga; Wang, Xu-Ming; Gutin, Alexey

2006-05-01

Panoramic cameras offer true real-time, 360-degree coverage of the surrounding area, valuable for a variety of defense and security applications, including force protection, asset protection, asset control, security including port security, perimeter security, video surveillance, border control, airport security, coastguard operations, search and rescue, intrusion detection, and many others. Automatic detection, location, and tracking of targets outside protected area ensures maximum protection and at the same time reduces the workload on personnel, increases reliability and confidence of target detection, and enables both man-in-the-loop and fully automated system operation. Thermal imaging provides the benefits of all-weather, 24-hour day/night operation with no downtime. In addition, thermal signatures of different target types facilitate better classification, beyond the limits set by camera's spatial resolution. The useful range of catadioptric panoramic cameras is affected by their limited resolution. In many existing systems the resolution is optics-limited. Reflectors customarily used in catadioptric imagers introduce aberrations that may become significant at large camera apertures, such as required in low-light and thermal imaging. Advantages of panoramic imagers with high image resolution include increased area coverage with fewer cameras, instantaneous full horizon detection, location and tracking of multiple targets simultaneously, extended range, and others. The Automatic Panoramic Thermal Integrated Sensor (APTIS), being jointly developed by Applied Science Innovative, Inc. (ASI) and the Armament Research, Development and Engineering Center (ARDEC) combines the strengths of improved, high-resolution panoramic optics with thermal imaging in the 8 - 14 micron spectral range, leveraged by intelligent video processing for automated detection, location, and tracking of moving targets. The work in progress supports the Future Combat Systems (FCS) and the Intelligent Munitions Systems (IMS). The APTIS is anticipated to operate as an intelligent node in a wireless network of multifunctional nodes that work together to serve in a wide range of applications of homeland security, as well as serve the Army in tasks of improved situational awareness (SA) in defense and offensive operations, and as a sensor node in tactical Intelligence Surveillance Reconnaissance (ISR). The novel ViperView TM high-resolution panoramic thermal imager is the heart of the APTIS system. It features an aberration-corrected omnidirectional imager with small optics designed to match the resolution of a 640x480 pixels IR camera with improved image quality for longer range target detection, classification, and tracking. The same approach is applicable to panoramic cameras working in the visible spectral range. Other components of the ATPIS system include network communications, advanced power management, and wakeup capability. Recent developments include image processing, optical design being expanded into the visible spectral range, and wireless communications design. This paper describes the development status of the APTIS system.

Human versus automation in responding to failures: an expected-value analysis

NASA Technical Reports Server (NTRS)

Sheridan, T. B.; Parasuraman, R.

2000-01-01

A simple analytical criterion is provided for deciding whether a human or automation is best for a failure detection task. The method is based on expected-value decision theory in much the same way as is signal detection. It requires specification of the probabilities of misses (false negatives) and false alarms (false positives) for both human and automation being considered, as well as factors independent of the choice--namely, costs and benefits of incorrect and correct decisions as well as the prior probability of failure. The method can also serve as a basis for comparing different modes of automation. Some limiting cases of application are discussed, as are some decision criteria other than expected value. Actual or potential applications include the design and evaluation of any system in which either humans or automation are being considered.

Automated detection and classification of dice

NASA Astrophysics Data System (ADS)

Correia, Bento A. B.; Silva, Jeronimo A.; Carvalho, Fernando D.; Guilherme, Rui; Rodrigues, Fernando C.; de Silva Ferreira, Antonio M.

1995-03-01

This paper describes a typical machine vision system in an unusual application, the automated visual inspection of a Casino's playing tables. The SORTE computer vision system was developed at INETI under a contract with the Portuguese Gaming Inspection Authorities IGJ. It aims to automate the tasks of detection and classification of the dice's scores on the playing tables of the game `Banca Francesa' (which means French Banking) in Casinos. The system is based on the on-line analysis of the images captured by a monochrome CCD camera placed over the playing tables, in order to extract relevant information concerning the score indicated by the dice. Image processing algorithms for real time automatic throwing detection and dice classification were developed and implemented.

Automated Detection of Optic Disc in Fundus Images

NASA Astrophysics Data System (ADS)

Burman, R.; Almazroa, A.; Raahemifar, K.; Lakshminarayanan, V.

Optic disc (OD) localization is an important preprocessing step in the automated image detection of fundus image infected with glaucoma. An Interval Type-II fuzzy entropy based thresholding scheme along with Differential Evolution (DE) is applied to determine the location of the OD in the right of left eye retinal fundus image. The algorithm, when applied to 460 fundus images from the MESSIDOR dataset, shows a success rate of 99.07 % for 217 normal images and 95.47 % for 243 pathological images. The mean computational time is 1.709 s for normal images and 1.753 s for pathological images. These results are important for automated detection of glaucoma and for telemedicine purposes.

Multi-Sensory Features for Personnel Detection at Border Crossings

DTIC Science & Technology

2011-07-08

challenging problem. Video sensors consume high amounts of power and require a large volume for storage. Hence, it is preferable to use non- imaging sensors...temporal distribution of gait beats [5]. At border crossings, animals such as mules, horses, or donkeys are often known to carry loads. Animal hoof...field, passive ultrasonic, sonar, and both infrared and visi- ble video sensors. Each sensor suite is placed along the path with a spacing of 40 to

Automatic detection of blood versus non-blood regions on intravascular ultrasound (IVUS) images using wavelet packet signatures

NASA Astrophysics Data System (ADS)

Katouzian, Amin; Baseri, Babak; Konofagou, Elisa E.; Laine, Andrew F.

2008-03-01

Intravascular ultrasound (IVUS) has been proven a reliable imaging modality that is widely employed in cardiac interventional procedures. It can provide morphologic as well as pathologic information on the occluded plaques in the coronary arteries. In this paper, we present a new technique using wavelet packet analysis that differentiates between blood and non-blood regions on the IVUS images. We utilized the multi-channel texture segmentation algorithm based on the discrete wavelet packet frames (DWPF). A k-mean clustering algorithm was deployed to partition the extracted textural features into blood and non-blood in an unsupervised fashion. Finally, the geometric and statistical information of the segmented regions was used to estimate the closest set of pixels to the lumen border and a spline curve was fitted to the set. The presented algorithm may be helpful in delineating the lumen border automatically and more reliably prior to the process of plaque characterization, especially with 40 MHz transducers, where appearance of the red blood cells renders the border detection more challenging, even manually. Experimental results are shown and they are quantitatively compared with manually traced borders by an expert. It is concluded that our two dimensional (2-D) algorithm, which is independent of the cardiac and catheter motions performs well in both in-vivo and in-vitro cases.

Automatic media-adventitia IVUS image segmentation based on sparse representation framework and dynamic directional active contour model.

PubMed

Zakeri, Fahimeh Sadat; Setarehdan, Seyed Kamaledin; Norouzi, Somayye

2017-10-01

Segmentation of the arterial wall boundaries from intravascular ultrasound images is an important image processing task in order to quantify arterial wall characteristics such as shape, area, thickness and eccentricity. Since manual segmentation of these boundaries is a laborious and time consuming procedure, many researchers attempted to develop (semi-) automatic segmentation techniques as a powerful tool for educational and clinical purposes in the past but as yet there is no any clinically approved method in the market. This paper presents a deterministic-statistical strategy for automatic media-adventitia border detection by a fourfold algorithm. First, a smoothed initial contour is extracted based on the classification in the sparse representation framework which is combined with the dynamic directional convolution vector field. Next, an active contour model is utilized for the propagation of the initial contour toward the interested borders. Finally, the extracted contour is refined in the leakage, side branch openings and calcification regions based on the image texture patterns. The performance of the proposed algorithm is evaluated by comparing the results to those manually traced borders by an expert on 312 different IVUS images obtained from four different patients. The statistical analysis of the results demonstrates the efficiency of the proposed method in the media-adventitia border detection with enough consistency in the leakage and calcification regions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Autonomous robot for detecting subsurface voids and tunnels using microgravity

NASA Astrophysics Data System (ADS)

Wilson, Stacy S.; Crawford, Nicholas C.; Croft, Leigh Ann; Howard, Michael; Miller, Stephen; Rippy, Thomas

2006-05-01

Tunnels have been used to evade security of defensive positions both during times of war and peace for hundreds of years. Tunnels are presently being built under the Mexican Border by drug smugglers and possibly terrorists. Several have been discovered at the border crossing at Nogales near Tucson, Arizona, along with others at other border towns. During this war on terror, tunnels under the Mexican Border pose a significant threat for the security of the United States. It is also possible that terrorists will attempt to tunnel under strategic buildings and possibly discharge explosives. The Center for Cave and Karst Study (CCKS) at Western Kentucky University has a long and successful history of determining the location of caves and subsurface voids using microgravity technology. Currently, the CCKS is developing a remotely controlled robot which will be used to locate voids underground. The robot will be a remotely controlled vehicle that will use microgravity and GPS to accurately detect and measure voids below the surface. It is hoped that this robot will also be used in military applications to locate other types of voids underground such as tunnels and bunkers. It is anticipated that the robot will be able to function up to a mile from the operator. This paper will describe the construction of the robot and the use of microgravity technology to locate subsurface voids with the robot.

Automated Micro-Object Detection for Mobile Diagnostics Using Lens-Free Imaging Technology

PubMed Central

Roy, Mohendra; Seo, Dongmin; Oh, Sangwoo; Chae, Yeonghun; Nam, Myung-Hyun; Seo, Sungkyu

2016-01-01

Lens-free imaging technology has been extensively used recently for microparticle and biological cell analysis because of its high throughput, low cost, and simple and compact arrangement. However, this technology still lacks a dedicated and automated detection system. In this paper, we describe a custom-developed automated micro-object detection method for a lens-free imaging system. In our previous work (Roy et al.), we developed a lens-free imaging system using low-cost components. This system was used to generate and capture the diffraction patterns of micro-objects and a global threshold was used to locate the diffraction patterns. In this work we used the same setup to develop an improved automated detection and analysis algorithm based on adaptive threshold and clustering of signals. For this purpose images from the lens-free system were then used to understand the features and characteristics of the diffraction patterns of several types of samples. On the basis of this information, we custom-developed an automated algorithm for the lens-free imaging system. Next, all the lens-free images were processed using this custom-developed automated algorithm. The performance of this approach was evaluated by comparing the counting results with standard optical microscope results. We evaluated the counting results for polystyrene microbeads, red blood cells, HepG2, HeLa, and MCF7 cells lines. The comparison shows good agreement between the systems, with a correlation coefficient of 0.91 and linearity slope of 0.877. We also evaluated the automated size profiles of the microparticle samples. This Wi-Fi-enabled lens-free imaging system, along with the dedicated software, possesses great potential for telemedicine applications in resource-limited settings. PMID:27164146

Proof of Concept of Automated Collision Detection Technology in Rugby Sevens.

PubMed

Clarke, Anthea C; Anson, Judith M; Pyne, David B

2017-04-01

Clarke, AC, Anson, JM, and Pyne, DB. Proof of concept of automated collision detection technology in rugby sevens. J Strength Cond Res 31(4): 1116-1120, 2017-Developments in microsensor technology allow for automated detection of collisions in various codes of football, removing the need for time-consuming postprocessing of video footage. However, little research is available on the ability of microsensor technology to be used across various sports or genders. Game video footage was matched with microsensor-detected collisions (GPSports) in one men's (n = 12 players) and one women's (n = 12) rugby sevens match. True-positive, false-positive, and false-negative events between video and microsensor-detected collisions were used to calculate recall (ability to detect a collision) and precision (accurately identify a collision). The precision was similar between the men's and women's rugby sevens game (∼0.72; scale 0.00-1.00); however, the recall in the women's game (0.45) was less than that for the men's game (0.69). This resulted in 45% of collisions for men and 62% of collisions for women being incorrectly labeled. Currently, the automated collision detection system in GPSports microtechnology units has only modest utility in rugby sevens, and it seems that a rugby sevens-specific algorithm is needed. Differences in measures between the men's and women's game may be a result of physical size, and strength, and physicality, as well as technical and tactical factors.

Automated Detection of Repetitive Motor Behaviors as an Outcome Measurement in Intellectual and Developmental Disabilities

ERIC Educational Resources Information Center

Gilchrist, Kristin H.; Hegarty-Craver, Meghan; Christian, Robert B.; Grego, Sonia; Kies, Ashley C.; Wheeler, Anne C.

2018-01-01

Repetitive sensory motor behaviors are a direct target for clinical treatment and a potential treatment endpoint for individuals with intellectual or developmental disabilities. By removing the burden associated with video annotation or direct observation, automated detection of stereotypy would allow for longer term monitoring in ecologic…

Validation of shortened 2-day sterility testing of mesenchymal stem cell-based therapeutic preparation on an automated culture system.

PubMed

Lysák, Daniel; Holubová, Monika; Bergerová, Tamara; Vávrová, Monika; Cangemi, Giuseppina Cristina; Ciccocioppo, Rachele; Kruzliak, Peter; Jindra, Pavel

2016-03-01

Cell therapy products represent a new trend of treatment in the field of immunotherapy and regenerative medicine. Their biological nature and multistep preparation procedure require the application of complex release criteria and quality control. Microbial contamination of cell therapy products is a potential source of morbidity in recipients. The automated blood culture systems are widely used for the detection of microorganisms in cell therapy products. However the standard 2-week cultivation period is too long for some cell-based treatments and alternative methods have to be devised. We tried to verify whether a shortened cultivation of the supernatant from the mesenchymal stem cell (MSC) culture obtained 2 days before the cell harvest could sufficiently detect microbial growth and allow the release of MSC for clinical application. We compared the standard Ph. Eur. cultivation method and the automated blood culture system BACTEC (Becton Dickinson). The time to detection (TTD) and the detection limit were analyzed for three bacterial and two fungal strains. The Staphylococcus aureus and Pseudomonas aeruginosa were recognized within 24 h with both methods (detection limit ~10 CFU). The time required for the detection of Bacillus subtilis was shorter with the automated method (TTD 10.3 vs. 60 h for 10-100 CFU). The BACTEC system reached significantly shorter times to the detection of Candida albicans and Aspergillus brasiliensis growth compared to the classical method (15.5 vs. 48 and 31.5 vs. 48 h, respectively; 10-100 CFU). The positivity was demonstrated within 48 h in all bottles, regardless of the size of the inoculum. This study validated the automated cultivation system as a method able to detect all tested microorganisms within a 48-h period with a detection limit of ~10 CFU. Only in case of B. subtilis, the lowest inoculum (~10 CFU) was not recognized. The 2-day cultivation technique is then capable of confirming the microbiological safety of MSC and allows their timely release for clinical application.

Model-based morphological segmentation and labeling of coronary angiograms.

PubMed

Haris, K; Efstratiadis, S N; Maglaveras, N; Pappas, C; Gourassas, J; Louridas, G

1999-10-01

A method for extraction and labeling of the coronary arterial tree (CAT) using minimal user supervision in single-view angiograms is proposed. The CAT structural description (skeleton and borders) is produced, along with quantitative information for the artery dimensions and assignment of coded labels, based on a given coronary artery model represented by a graph. The stages of the method are: 1) CAT tracking and detection; 2) artery skeleton and border estimation; 3) feature graph creation; and iv) artery labeling by graph matching. The approximate CAT centerline and borders are extracted by recursive tracking based on circular template analysis. The accurate skeleton and borders of each CAT segment are computed, based on morphological homotopy modification and watershed transform. The approximate centerline and borders are used for constructing the artery segment enclosing area (ASEA), where the defined skeleton and border curves are considered as markers. Using the marked ASEA, an artery gradient image is constructed where all the ASEA pixels (except the skeleton ones) are assigned the gradient magnitude of the original image. The artery gradient image markers are imposed as its unique regional minima by the homotopy modification method, the watershed transform is used for extracting the artery segment borders, and the feature graph is updated. Finally, given the created feature graph and the known model graph, a graph matching algorithm assigns the appropriate labels to the extracted CAT using weighted maximal cliques on the association graph corresponding to the two given graphs. Experimental results using clinical digitized coronary angiograms are presented.

Progress in Fully Automated Abdominal CT Interpretation

PubMed Central

Summers, Ronald M.

2016-01-01

OBJECTIVE Automated analysis of abdominal CT has advanced markedly over just the last few years. Fully automated assessment of organs, lymph nodes, adipose tissue, muscle, bowel, spine, and tumors are some examples where tremendous progress has been made. Computer-aided detection of lesions has also improved dramatically. CONCLUSION This article reviews the progress and provides insights into what is in store in the near future for automated analysis for abdominal CT, ultimately leading to fully automated interpretation. PMID:27101207

Automated aortic calcification detection in low-dose chest CT images

NASA Astrophysics Data System (ADS)

Xie, Yiting; Htwe, Yu Maw; Padgett, Jennifer; Henschke, Claudia; Yankelevitz, David; Reeves, Anthony P.

2014-03-01

The extent of aortic calcification has been shown to be a risk indicator for vascular events including cardiac events. We have developed a fully automated computer algorithm to segment and measure aortic calcification in low-dose noncontrast, non-ECG gated, chest CT scans. The algorithm first segments the aorta using a pre-computed Anatomy Label Map (ALM). Then based on the segmented aorta, aortic calcification is detected and measured in terms of the Agatston score, mass score, and volume score. The automated scores are compared with reference scores obtained from manual markings. For aorta segmentation, the aorta is modeled as a series of discrete overlapping cylinders and the aortic centerline is determined using a cylinder-tracking algorithm. Then the aortic surface location is detected using the centerline and a triangular mesh model. The segmented aorta is used as a mask for the detection of aortic calcification. For calcification detection, the image is first filtered, then an elevated threshold of 160 Hounsfield units (HU) is used within the aorta mask region to reduce the effect of noise in low-dose scans, and finally non-aortic calcification voxels (bony structures, calcification in other organs) are eliminated. The remaining candidates are considered as true aortic calcification. The computer algorithm was evaluated on 45 low-dose non-contrast CT scans. Using linear regression, the automated Agatston score is 98.42% correlated with the reference Agatston score. The automated mass and volume score is respectively 98.46% and 98.28% correlated with the reference mass and volume score.

Imaging Analysis of Hepatoblastoma Resectability Across Neoadjuvant Chemotherapy

PubMed Central

Murphy, Andrew J.; Ayers, Gregory D.; Hilmes, Melissa A.; Mukherjee, Kaushik; Wilson, Kevin J.; Allen, Wade M.; Fernandez-Pineda, Israel; Shinall, Myrick C.; Zhao, Zhiguo; Furman, Wayne L.; McCarville, Mary Beth; Davidoff, Andrew M.; Lovvorn, Harold N.

2013-01-01

Purpose Hepatoblastomas often require neoadjuvant chemotherapy to facilitate partial hepatectomy, which necessitates freedom of tumor borders from the confluence of hepatic veins (COHV), portal vein bifurcation (PVB), and retrohepatic inferior vena cava (IVC). This study aimed to clarify the effect of incremental neoadjuvant cycles on the AHEP0731 protocol criteria of hepatoblastoma resectability. Methods Hepatoblastoma responses to neoadjuvant chemotherapy were analyzed among patients (n=23) treated at two children’s hospitals between 1996 and 2010. Using digital imaging data, ellipsoid and point-based models were created to measure tumor volume regression and respective distances from tumor borders nearest to the COHV, PVB, and IVC. Results Hepatoblastoma volumes regressed with incremental neoadjuvant chemotherapy cycles (p<0.001). Although tumor borders regressed away from the COHV (p=0.008), on average only 1.1mm was gained. No change from tumor borders to the PVB was detected (p=0.102). Distances from tumor borders to the IVC remained stable at one hospital (p=0.612), but increased only 0.15mm every 10 days of therapy at the other (p=0.002). Neoadjuvant chemotherapy induced slightly more tumors to meet the threshold vascular margin of 1cm (baseline to completion): COHV, 11 (47.8%) to 17 (73.9%; p=0.058); PVB, 11 (47.8%) to 15 (65.2%; p=0.157); IVC, 4 (17.4%) to 10 (43.5%; p=0.034). No differences were detected in demographic or disease-specific characteristics between patients who did or did not achieve this 1cm margin after conclusion of chemotherapy. Conclusion Hepatoblastoma volumes regress significantly with increasing neoadjuvant chemotherapy cycles. However, tumors often remain anchored to the major hepatic vasculature, showing marginal improvement in resectability criteria. PMID:23845613

A DRIED BLOOD SPOT METHOD TO EVALUATE CHOLINESTERASE ACTIVITY IN YOUNG CHILDREN

EPA Science Inventory

Field methods are needed to detect and monitor anticholinesterase pesticide exposure of young children. Twenty children, aged 11-18 months, living in an agricultural community along the US/Mexico border were enrolled in a pilot study investigating methods to detect pesticide expo...

Automated search of control points in surface-based morphometry.

PubMed

Canna, Antonietta; Russo, Andrea G; Ponticorvo, Sara; Manara, Renzo; Pepino, Alessandro; Sansone, Mario; Di Salle, Francesco; Esposito, Fabrizio

2018-04-16

Cortical surface-based morphometry is based on a semi-automated analysis of structural MRI images. In FreeSurfer, a widespread tool for surface-based analyses, a visual check of gray-white matter borders is followed by the manual placement of control points to drive the topological correction (editing) of segmented data. A novel algorithm combining radial sampling and machine learning is presented for the automated control point search (ACPS). Four data sets with 3 T MRI structural images were used for ACPS validation, including raw data acquired twice in 36 healthy subjects and both raw and FreeSurfer preprocessed data of 125 healthy subjects from public databases. The unedited data from a subgroup of subjects were submitted to manual control point search and editing. The ACPS algorithm was trained on manual control points and tested on new (unseen) unedited data. Cortical thickness (CT) and fractal dimensionality (FD) were estimated in three data sets by reconstructing surfaces from both unedited and edited data, and the effects of editing were compared between manual and automated editing and versus no editing. The ACPS-based editing improved the surface reconstructions similarly to manual editing. Compared to no editing, ACPS-based and manual editing significantly reduced CT and FD in consistent regions across different data sets. Despite the extra processing of control point driven reconstructions, CT and FD estimates were highly reproducible in almost all cortical regions, albeit some problematic regions (e.g. entorhinal cortex) may benefit from different editing. The use of control points improves the surface reconstruction and the ACPS algorithm can automate their search reducing the burden of manual editing. Copyright © 2018 Elsevier Inc. All rights reserved.

Two Automated Techniques for Carotid Lumen Diameter Measurement: Regional versus Boundary Approaches.

PubMed

Araki, Tadashi; Kumar, P Krishna; Suri, Harman S; Ikeda, Nobutaka; Gupta, Ajay; Saba, Luca; Rajan, Jeny; Lavra, Francesco; Sharma, Aditya M; Shafique, Shoaib; Nicolaides, Andrew; Laird, John R; Suri, Jasjit S

2016-07-01

The degree of stenosis in the carotid artery can be predicted using automated carotid lumen diameter (LD) measured from B-mode ultrasound images. Systolic velocity-based methods for measurement of LD are subjective. With the advancement of high resolution imaging, image-based methods have started to emerge. However, they require robust image analysis for accurate LD measurement. This paper presents two different algorithms for automated segmentation of the lumen borders in carotid ultrasound images. Both algorithms are modeled as a two stage process. Stage one consists of a global-based model using scale-space framework for the extraction of the region of interest. This stage is common to both algorithms. Stage two is modeled using a local-based strategy that extracts the lumen interfaces. At this stage, the algorithm-1 is modeled as a region-based strategy using a classification framework, whereas the algorithm-2 is modeled as a boundary-based approach that uses the level set framework. Two sets of databases (DB), Japan DB (JDB) (202 patients, 404 images) and Hong Kong DB (HKDB) (50 patients, 300 images) were used in this study. Two trained neuroradiologists performed manual LD tracings. The mean automated LD measured was 6.35 ± 0.95 mm for JDB and 6.20 ± 1.35 mm for HKDB. The precision-of-merit was: 97.4 % and 98.0 % w.r.t to two manual tracings for JDB and 99.7 % and 97.9 % w.r.t to two manual tracings for HKDB. Statistical tests such as ANOVA, Chi-Squared, T-test, and Mann-Whitney test were conducted to show the stability and reliability of the automated techniques.

Development and Validation of an Automated High-Throughput System for Zebrafish In Vivo Screenings

PubMed Central

Virto, Juan M.; Holgado, Olaia; Diez, Maria; Izpisua Belmonte, Juan Carlos; Callol-Massot, Carles

2012-01-01

The zebrafish is a vertebrate model compatible with the paradigms of drug discovery. The small size and transparency of zebrafish embryos make them amenable for the automation necessary in high-throughput screenings. We have developed an automated high-throughput platform for in vivo chemical screenings on zebrafish embryos that includes automated methods for embryo dispensation, compound delivery, incubation, imaging and analysis of the results. At present, two different assays to detect cardiotoxic compounds and angiogenesis inhibitors can be automatically run in the platform, showing the versatility of the system. A validation of these two assays with known positive and negative compounds, as well as a screening for the detection of unknown anti-angiogenic compounds, have been successfully carried out in the system developed. We present a totally automated platform that allows for high-throughput screenings in a vertebrate organism. PMID:22615792

Automated Processing of 2-D Gel Electrophoretograms of Genomic DNA for Hunting Pathogenic DNA Molecular Changes.

PubMed

Takahashi; Nakazawa; Watanabe; Konagaya

1999-01-01

We have developed the automated processing algorithms for 2-dimensional (2-D) electrophoretograms of genomic DNA based on RLGS (Restriction Landmark Genomic Scanning) method, which scans the restriction enzyme recognition sites as the landmark and maps them onto a 2-D electrophoresis gel. Our powerful processing algorithms realize the automated spot recognition from RLGS electrophoretograms and the automated comparison of a huge number of such images. In the final stage of the automated processing, a master spot pattern, on which all the spots in the RLGS images are mapped at once, can be obtained. The spot pattern variations which seemed to be specific to the pathogenic DNA molecular changes can be easily detected by simply looking over the master spot pattern. When we applied our algorithms to the analysis of 33 RLGS images derived from human colon tissues, we successfully detected several colon tumor specific spot pattern changes.

Cross-Border Cholera Outbreaks in Sub-Saharan Africa, the Mystery behind the Silent Illness: What Needs to Be Done?

PubMed Central

Mwesawina, Maurice; Baluku, Yosia; Kanyanda, Setiala S. E.; Orach, Christopher Garimoi

2016-01-01

Introduction Cross-border cholera outbreaks are a major public health problem in Sub-Saharan Africa contributing to the high annual reported cholera cases and deaths. These outbreaks affect all categories of people and are challenging to prevent and control. This article describes lessons learnt during the cross-border cholera outbreak control in Eastern and Southern Africa sub-regions using the case of Uganda-DRC and Malawi-Mozambique borders and makes recommendations for future outbreak prevention and control. Materials and Methods We reviewed weekly surveillance data, outbreak response reports and documented experiences on the management of the most recent cross-border cholera outbreaks in Eastern and Southern Africa sub-regions, namely in Uganda and Malawi respectively. Uganda-Democratic Republic of Congo and Malawi-Mozambique borders were selected because the countries sharing these borders reported high cholera disease burden to WHO. Results A total of 603 cross-border cholera cases with 5 deaths were recorded in Malawi and Uganda in 2015. Uganda recorded 118 cases with 2 deaths and CFR of 1.7%. The under-fives and school going children were the most affected age groups contributing 24.2% and 36.4% of all patients seen along Malawi-Mozambique and Uganda-DRC borders, respectively. These outbreaks lasted for over 3 months and spread to new areas leading to 60 cases with 3 deaths, CRF of 5%, and 102 cases 0 deaths in Malawi and Uganda, respectively. Factors contributing to these outbreaks were: poor sanitation and hygiene, use of contaminated water, floods and rampant cross-border movements. The outbreak control efforts mainly involved unilateral measures implemented by only one of the affected countries. Conclusions Cross-border cholera outbreaks contribute to the high annual reported cholera burden in Sub-Saharan Africa yet they remain silent, marginalized and poorly identified by cholera actors (governments and international agencies). The under-fives and the school going children were the most affected age groups. To successfully prevent and control these outbreaks, guidelines and strategies should be reviewed to assign clear roles and responsibilities to cholera actors on collaboration, prevention, detection, monitoring and control of these epidemics. PMID:27258124

A 20-year catalog comparing smooth and sharp estimates of slow slip events in Cascadia

NASA Astrophysics Data System (ADS)

Molitors Bergman, E. G.; Evans, E. L.; Loveless, J. P.

2017-12-01

Slow slip events (SSEs) are a form of aseismic strain release at subduction zones resulting in a temporary reversal in interseismic upper plate motion over a period of weeks, frequently accompanied in time and space by seismic tremor at the Cascadia subduction zone. Locating SSEs spatially along the subduction zone interface is essential to understanding the relationship between SSEs, earthquakes, and tremor and assessing megathrust earthquake hazard. We apply an automated slope comparison-based detection algorithm to single continuously recording GPS stations to determine dates and surface displacement vectors of SSEs, then apply network-based filters to eliminate false detections. The main benefits of this algorithm are its ability to detect SSEs while they are occurring and track the spatial migration of each event. We invert geodetic displacement fields for slip distributions on the subduction zone interface for SSEs between 1997 and 2017 using two estimation techniques: spatial smoothing and total variation regularization (TVR). Smoothing has been frequently used in determining the location of interseismic coupling, earthquake rupture, and SSE slip and yields spatially coherent but inherently blurred solutions. TVR yields compact, sharply bordered slip estimates of similar magnitude and along-strike extent to previously presented studied events, while fitting the constraining geodetic data as well as corresponding smoothing-based solutions. Slip distributions estimated using TVR have up-dip limits that align well with down-dip limits of interseismic coupling on the plate interface and spatial extents that approximately correspond to the distribution of tremor concurrent with each event. TVR gives a unique view of slow slip distributions that can contribute to understanding of the physical properties that govern megathrust slip processes.

Transmission Dynamics, Border Entry Screening, and School Holidays during the 2009 Influenza A (H1N1) Pandemic, China

PubMed Central

Yu, Hongjie; Cauchemez, Simon; Donnelly, Christl A.; Zhou, Lei; Feng, Luzhao; Xiang, Nijuan; Zheng, Jiandong; Ye, Min; Huai, Yang; Liao, Qiaohong; Peng, Zhibin; Feng, Yunxia; Jiang, Hui; Yang, Weizhong; Wang, Yu; Feng, Zijian

2012-01-01

Pandemic influenza A (H1N1) 2009 virus spread rapidly around the world in 2009. We used multiple data sources from surveillance systems and specific investigations to characterize the transmission patterns of this virus in China during May–November 2009 and analyze the effectiveness of border entry screening and holiday-related school closures on transmission. In China, age distribution and transmission dynamic characteristics were similar to those in Northern Hemisphere temperate countries. The epidemic was focused in children, with an effective reproduction number of ≈1.2–1.3. The 8 days of national holidays in October reduced the effective reproduction number by 37% (95% credible interval 28%–45%) and increased underreporting by ≈20%–30%. Border entry screening detected at most 37% of international travel–related cases, with most (89%) persons identified as having fever at time of entry. These findings suggest that border entry screening was unlikely to have delayed spread in China by >4 days. PMID:22515989

Automated Detection of Heuristics and Biases among Pathologists in a Computer-Based System

ERIC Educational Resources Information Center

Crowley, Rebecca S.; Legowski, Elizabeth; Medvedeva, Olga; Reitmeyer, Kayse; Tseytlin, Eugene; Castine, Melissa; Jukic, Drazen; Mello-Thoms, Claudia

2013-01-01

The purpose of this study is threefold: (1) to develop an automated, computer-based method to detect heuristics and biases as pathologists examine virtual slide cases, (2) to measure the frequency and distribution of heuristics and errors across three levels of training, and (3) to examine relationships of heuristics to biases, and biases to…

A comparison of automated crater detection methods

NASA Astrophysics Data System (ADS)

Bandeira, L.; Barreira, C.; Pina, P.; Saraiva, J.

2008-09-01

Abstract This work presents early results of a comparison between some common methodologies for automated crater detection. The three procedures considered were applied to images of the surface of Mars, thus illustrating some pros and cons of their use. We aim to establish the clear advantages in using this type of methods in the study of planetary surfaces.

A neural model of border-ownership from kinetic occlusion.

PubMed

Layton, Oliver W; Yazdanbakhsh, Arash

2015-01-01

Camouflaged animals that have very similar textures to their surroundings are difficult to detect when stationary. However, when an animal moves, humans readily see a figure at a different depth than the background. How do humans perceive a figure breaking camouflage, even though the texture of the figure and its background may be statistically identical in luminance? We present a model that demonstrates how the primate visual system performs figure-ground segregation in extreme cases of breaking camouflage based on motion alone. Border-ownership signals develop as an emergent property in model V2 units whose receptive fields are nearby kinetically defined borders that separate the figure and background. Model simulations support border-ownership as a general mechanism by which the visual system performs figure-ground segregation, despite whether figure-ground boundaries are defined by luminance or motion contrast. The gradient of motion- and luminance-related border-ownership signals explains the perceived depth ordering of the foreground and background surfaces. Our model predicts that V2 neurons, which are sensitive to kinetic edges, are selective to border-ownership (magnocellular B cells). A distinct population of model V2 neurons is selective to border-ownership in figures defined by luminance contrast (parvocellular B cells). B cells in model V2 receive feedback from neurons in V4 and MT with larger receptive fields to bias border-ownership signals toward the figure. We predict that neurons in V4 and MT sensitive to kinetically defined figures play a crucial role in determining whether the foreground surface accretes, deletes, or produces a shearing motion with respect to the background. Copyright © 2014 Elsevier Ltd. All rights reserved.

Phase II: Automated System for Aneuploidy Detection in Sperm Final Report CRADA No. TC-1554-98

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wyrobek, W. J.; Dunlay, R. T.

This was a collaborative effort between the University of California, Lawrence Livermore National Laboratory (LLNL) and Cellomics, Inc. (formerly BioDx and Biological Detection, Inc.) to develop an automated system for detecting human sperm aneuploidy. Aneuploidy (an abnormal number of chromosomes) is one of the major categories of chromosomally abnormal sperm, which results in chromosomally defective pregnancies and babies. An automated system would be used for testing the effects of toxic agents and for other research and clinical applications. This collaborated effort was funded by a National Institutes of Environmental Health Services, Phase II, Small Business Innovation Research Program (SBIR) grantmore » to Cellornics (Contract No. N44-ES-82004).« less

Development of a Miniature Mass Spectrometer and an Automated Detector for Sampling Explosive Materials

PubMed Central

Hashimoto, Yuichiro

2017-01-01

The development of a robust ionization source using the counter-flow APCI, miniature mass spectrometer, and an automated sampling system for detecting explosives are described. These development efforts using mass spectrometry were made in order to improve the efficiencies of on-site detection in areas such as security, environmental, and industrial applications. A development team, including the author, has struggled for nearly 20 years to enhance the robustness and reduce the size of mass spectrometers to meet the requirements needed for on-site applications. This article focuses on the recent results related to the detection of explosive materials where automated particle sampling using a cyclone concentrator permitted the inspection time to be successfully reduced to 3 s. PMID:28337396

21 CFR 864.9300 - Automated Coombs test systems.

Code of Federal Regulations, 2013 CFR

2013-04-01

... Blood and Blood Products § 864.9300 Automated Coombs test systems. (a) Identification. An automated Coombs test system is a device used to detect and identify antibodies in patient sera or antibodies bound to red cells. The Coombs test is used for the diagnosis of hemolytic disease of the newborn, and...

21 CFR 864.9300 - Automated Coombs test systems.

Code of Federal Regulations, 2012 CFR

2012-04-01

... Blood and Blood Products § 864.9300 Automated Coombs test systems. (a) Identification. An automated Coombs test system is a device used to detect and identify antibodies in patient sera or antibodies bound to red cells. The Coombs test is used for the diagnosis of hemolytic disease of the newborn, and...

21 CFR 864.9300 - Automated Coombs test systems.

Code of Federal Regulations, 2011 CFR

2011-04-01

... Blood and Blood Products § 864.9300 Automated Coombs test systems. (a) Identification. An automated Coombs test system is a device used to detect and identify antibodies in patient sera or antibodies bound to red cells. The Coombs test is used for the diagnosis of hemolytic disease of the newborn, and...

21 CFR 864.9300 - Automated Coombs test systems.

Code of Federal Regulations, 2010 CFR

2010-04-01

... Blood and Blood Products § 864.9300 Automated Coombs test systems. (a) Identification. An automated Coombs test system is a device used to detect and identify antibodies in patient sera or antibodies bound to red cells. The Coombs test is used for the diagnosis of hemolytic disease of the newborn, and...

21 CFR 864.9300 - Automated Coombs test systems.

Code of Federal Regulations, 2014 CFR

2014-04-01

... Blood and Blood Products § 864.9300 Automated Coombs test systems. (a) Identification. An automated Coombs test system is a device used to detect and identify antibodies in patient sera or antibodies bound to red cells. The Coombs test is used for the diagnosis of hemolytic disease of the newborn, and...

Automated Power-Distribution System

NASA Technical Reports Server (NTRS)

Ashworth, Barry; Riedesel, Joel; Myers, Chris; Miller, William; Jones, Ellen F.; Freeman, Kenneth; Walsh, Richard; Walls, Bryan K.; Weeks, David J.; Bechtel, Robert T.

1992-01-01

Autonomous power-distribution system includes power-control equipment and automation equipment. System automatically schedules connection of power to loads and reconfigures itself when it detects fault. Potential terrestrial applications include optimization of consumption of power in homes, power supplies for autonomous land vehicles and vessels, and power supplies for automated industrial processes.

Automated face detection for occurrence and occupancy estimation in chimpanzees.

PubMed

Crunchant, Anne-Sophie; Egerer, Monika; Loos, Alexander; Burghardt, Tilo; Zuberbühler, Klaus; Corogenes, Katherine; Leinert, Vera; Kulik, Lars; Kühl, Hjalmar S

2017-03-01

Surveying endangered species is necessary to evaluate conservation effectiveness. Camera trapping and biometric computer vision are recent technological advances. They have impacted on the methods applicable to field surveys and these methods have gained significant momentum over the last decade. Yet, most researchers inspect footage manually and few studies have used automated semantic processing of video trap data from the field. The particular aim of this study is to evaluate methods that incorporate automated face detection technology as an aid to estimate site use of two chimpanzee communities based on camera trapping. As a comparative baseline we employ traditional manual inspection of footage. Our analysis focuses specifically on the basic parameter of occurrence where we assess the performance and practical value of chimpanzee face detection software. We found that the semi-automated data processing required only 2-4% of the time compared to the purely manual analysis. This is a non-negligible increase in efficiency that is critical when assessing the feasibility of camera trap occupancy surveys. Our evaluations suggest that our methodology estimates the proportion of sites used relatively reliably. Chimpanzees are mostly detected when they are present and when videos are filmed in high-resolution: the highest recall rate was 77%, for a false alarm rate of 2.8% for videos containing only chimpanzee frontal face views. Certainly, our study is only a first step for transferring face detection software from the lab into field application. Our results are promising and indicate that the current limitation of detecting chimpanzees in camera trap footage due to lack of suitable face views can be easily overcome on the level of field data collection, that is, by the combined placement of multiple high-resolution cameras facing reverse directions. This will enable to routinely conduct chimpanzee occupancy surveys based on camera trapping and semi-automated processing of footage. Using semi-automated ape face detection technology for processing camera trap footage requires only 2-4% of the time compared to manual analysis and allows to estimate site use by chimpanzees relatively reliably. © 2017 Wiley Periodicals, Inc.

Integrating Online and Offline Three-Dimensional Deep Learning for Automated Polyp Detection in Colonoscopy Videos.

PubMed

Lequan Yu; Hao Chen; Qi Dou; Jing Qin; Pheng Ann Heng

2017-01-01

Automated polyp detection in colonoscopy videos has been demonstrated to be a promising way for colorectal cancer prevention and diagnosis. Traditional manual screening is time consuming, operator dependent, and error prone; hence, automated detection approach is highly demanded in clinical practice. However, automated polyp detection is very challenging due to high intraclass variations in polyp size, color, shape, and texture, and low interclass variations between polyps and hard mimics. In this paper, we propose a novel offline and online three-dimensional (3-D) deep learning integration framework by leveraging the 3-D fully convolutional network (3D-FCN) to tackle this challenging problem. Compared with the previous methods employing hand-crafted features or 2-D convolutional neural network, the 3D-FCN is capable of learning more representative spatio-temporal features from colonoscopy videos, and hence has more powerful discrimination capability. More importantly, we propose a novel online learning scheme to deal with the problem of limited training data by harnessing the specific information of an input video in the learning process. We integrate offline and online learning to effectively reduce the number of false positives generated by the offline network and further improve the detection performance. Extensive experiments on the dataset of MICCAI 2015 Challenge on Polyp Detection demonstrated the better performance of our method when compared with other competitors.

Automated crack detection in conductive smart-concrete structures using a resistor mesh model

NASA Astrophysics Data System (ADS)

Downey, Austin; D'Alessandro, Antonella; Ubertini, Filippo; Laflamme, Simon

2018-03-01

Various nondestructive evaluation techniques are currently used to automatically detect and monitor cracks in concrete infrastructure. However, these methods often lack the scalability and cost-effectiveness over large geometries. A solution is the use of self-sensing carbon-doped cementitious materials. These self-sensing materials are capable of providing a measurable change in electrical output that can be related to their damage state. Previous work by the authors showed that a resistor mesh model could be used to track damage in structural components fabricated from electrically conductive concrete, where damage was located through the identification of high resistance value resistors in a resistor mesh model. In this work, an automated damage detection strategy that works through placing high value resistors into the previously developed resistor mesh model using a sequential Monte Carlo method is introduced. Here, high value resistors are used to mimic the internal condition of damaged cementitious specimens. The proposed automated damage detection method is experimentally validated using a 500 × 500 × 50 mm3 reinforced cement paste plate doped with multi-walled carbon nanotubes exposed to 100 identical impact tests. Results demonstrate that the proposed Monte Carlo method is capable of detecting and localizing the most prominent damage in a structure, demonstrating that automated damage detection in smart-concrete structures is a promising strategy for real-time structural health monitoring of civil infrastructure.

Automated detection of abnormalities in paranasal sinus on dental panoramic radiographs by using contralateral subtraction technique based on mandible contour

NASA Astrophysics Data System (ADS)

Mori, Shintaro; Hara, Takeshi; Tagami, Motoki; Muramatsu, Chicako; Kaneda, Takashi; Katsumata, Akitoshi; Fujita, Hiroshi

2013-02-01

Inflammation in paranasal sinus sometimes becomes chronic to take long terms for the treatment. The finding is important for the early treatment, but general dentists may not recognize the findings because they focus on teeth treatments. The purpose of this study was to develop a computer-aided detection (CAD) system for the inflammation in paranasal sinus on dental panoramic radiographs (DPRs) by using the mandible contour and to demonstrate the potential usefulness of the CAD system by means of receiver operating characteristic analysis. The detection scheme consists of 3 steps: 1) Contour extraction of mandible, 2) Contralateral subtraction, and 3) Automated detection. The Canny operator and active contour model were applied to extract the edge at the first step. At the subtraction step, the right region of the extracted contour image was flipped to compare with the left region. Mutual information between two selected regions was obtained to estimate the shift parameters of image registration. The subtraction images were generated based on the shift parameter. Rectangle regions of left and right paranasal sinus on the subtraction image were determined based on the size of mandible. The abnormal side of the regions was determined by taking the difference between the averages of each region. Thirteen readers were responded to all cases without and with the automated results. The averaged AUC of all readers was increased from 0.69 to 0.73 with statistical significance (p=0.032) when the automated detection results were provided. In conclusion, the automated detection method based on contralateral subtraction technique improves readers' interpretation performance of inflammation in paranasal sinus on DPRs.

Fusion of multiple quadratic penalty function support vector machines (QPFSVM) for automated sea mine detection and classification

NASA Astrophysics Data System (ADS)

Dobeck, Gerald J.; Cobb, J. Tory

2002-08-01

The high-resolution sonar is one of the principal sensors used by the Navy to detect and classify sea mines in minehunting operations. For such sonar systems, substantial effort has been devoted to the development of automated detection and classification (D/C) algorithms. These have been spurred by several factors including (1) aids for operators to reduce work overload, (2) more optimal use of all available data, and (3) the introduction of unmanned minehunting systems. The environments where sea mines are typically laid (harbor areas, shipping lanes, and the littorals) give rise to many false alarms caused by natural, biologic, and man-made clutter. The objective of the automated D/C algorithms is to eliminate most of these false alarms while still maintaining a very high probability of mine detection and classification (PdPc). In recent years, the benefits of fusing the outputs of multiple D/C algorithms have been studied. We refer to this as Algorithm Fusion. The results have been remarkable, including reliable robustness to new environments. The Quadratic Penalty Function Support Vector Machine (QPFSVM) algorithm to aid in the automated detection and classification of sea mines is introduced in this paper. The QPFSVM algorithm is easy to train, simple to implement, and robust to feature space dimension. Outputs of successive SVM algorithms are cascaded in stages (fused) to improve the Probability of Classification (Pc) and reduce the number of false alarms. Even though our experience has been gained in the area of sea mine detection and classification, the principles described herein are general and can be applied to fusion of any D/C problem (e.g., automated medical diagnosis or automatic target recognition for ballistic missile defense).

Level of Automation and Failure Frequency Effects on Simulated Lunar Lander Performance

NASA Technical Reports Server (NTRS)

Marquez, Jessica J.; Ramirez, Margarita

2014-01-01

A human-in-the-loop experiment was conducted at the NASA Ames Research Center Vertical Motion Simulator, where instrument-rated pilots completed a simulated terminal descent phase of a lunar landing. Ten pilots participated in a 2 x 2 mixed design experiment, with level of automation as the within-subjects factor and failure frequency as the between subjects factor. The two evaluated levels of automation were high (fully automated landing) and low (manual controlled landing). During test trials, participants were exposed to either a high number of failures (75% failure frequency) or low number of failures (25% failure frequency). In order to investigate the pilots' sensitivity to changes in levels of automation and failure frequency, the dependent measure selected for this experiment was accuracy of failure diagnosis, from which D Prime and Decision Criterion were derived. For each of the dependent measures, no significant difference was found for level of automation and no significant interaction was detected between level of automation and failure frequency. A significant effect was identified for failure frequency suggesting failure frequency has a significant effect on pilots' sensitivity to failure detection and diagnosis. Participants were more likely to correctly identify and diagnose failures if they experienced the higher levels of failures, regardless of level of automation

A Fully Automated Method to Detect and Segment a Manufactured Object in an Underwater Color Image

NASA Astrophysics Data System (ADS)

Barat, Christian; Phlypo, Ronald

2010-12-01

We propose a fully automated active contours-based method for the detection and the segmentation of a moored manufactured object in an underwater image. Detection of objects in underwater images is difficult due to the variable lighting conditions and shadows on the object. The proposed technique is based on the information contained in the color maps and uses the visual attention method, combined with a statistical approach for the detection and an active contour for the segmentation of the object to overcome the above problems. In the classical active contour method the region descriptor is fixed and the convergence of the method depends on the initialization. With our approach, this dependence is overcome with an initialization using the visual attention results and a criterion to select the best region descriptor. This approach improves the convergence and the processing time while providing the advantages of a fully automated method.

Counterflow Dielectrophoresis for Trypanosome Enrichment and Detection in Blood

NASA Astrophysics Data System (ADS)

Menachery, Anoop; Kremer, Clemens; Wong, Pui E.; Carlsson, Allan; Neale, Steven L.; Barrett, Michael P.; Cooper, Jonathan M.

2012-10-01

Human African trypanosomiasis or sleeping sickness is a deadly disease endemic in sub-Saharan Africa, caused by single-celled protozoan parasites. Although it has been targeted for elimination by 2020, this will only be realized if diagnosis can be improved to enable identification and treatment of afflicted patients. Existing techniques of detection are restricted by their limited field-applicability, sensitivity and capacity for automation. Microfluidic-based technologies offer the potential for highly sensitive automated devices that could achieve detection at the lowest levels of parasitemia and consequently help in the elimination programme. In this work we implement an electrokinetic technique for the separation of trypanosomes from both mouse and human blood. This technique utilises differences in polarisability between the blood cells and trypanosomes to achieve separation through opposed bi-directional movement (cell counterflow). We combine this enrichment technique with an automated image analysis detection algorithm, negating the need for a human operator.

Automated measurement of office, home and ambulatory blood pressure in atrial fibrillation.

PubMed

Kollias, Anastasios; Stergiou, George S

2014-01-01

1. Hypertension and atrial fibrillation (AF) often coexist and are strong risk factors for stroke. Current guidelines for blood pressure (BP) measurement in AF recommend repeated measurements using the auscultatory method, whereas the accuracy of the automated devices is regarded as questionable. This review presents the current evidence on the feasibility and accuracy of automated BP measurement in the presence of AF and the potential for automated detection of undiagnosed AF during such measurements. 2. Studies evaluating the use of automated BP monitors in AF are limited and have significant heterogeneity in methodology and protocols. Overall, the oscillometric method is feasible for static (office or home) and ambulatory use and appears to be more accurate for systolic than diastolic BP measurement. 3. Given that systolic hypertension is particularly common and important in the elderly, the automated BP measurement method may be acceptable for self-home and ambulatory monitoring, but not for professional office or clinic measurement. 4. An embedded algorithm for the detection of asymptomatic AF during routine automated BP measurement with high diagnostic accuracy has been developed and appears to be a useful screening tool for elderly hypertensives. © 2013 Wiley Publishing Asia Pty Ltd.

An Automated Cloud-edge Detection Algorithm Using Cloud Physics and Radar Data

NASA Technical Reports Server (NTRS)

Ward, Jennifer G.; Merceret, Francis J.; Grainger, Cedric A.

2003-01-01

An automated cloud edge detection algorithm was developed and extensively tested. The algorithm uses in-situ cloud physics data measured by a research aircraft coupled with ground-based weather radar measurements to determine whether the aircraft is in or out of cloud. Cloud edges are determined when the in/out state changes, subject to a hysteresis constraint. The hysteresis constraint prevents isolated transient cloud puffs or data dropouts from being identified as cloud boundaries. The algorithm was verified by detailed manual examination of the data set in comparison to the results from application of the automated algorithm.

Automated clinical system for chromosome analysis

NASA Technical Reports Server (NTRS)

Castleman, K. R.; Friedan, H. J.; Johnson, E. T.; Rennie, P. A.; Wall, R. J. (Inventor)

1978-01-01

An automatic chromosome analysis system is provided wherein a suitably prepared slide with chromosome spreads thereon is placed on the stage of an automated microscope. The automated microscope stage is computer operated to move the slide to enable detection of chromosome spreads on the slide. The X and Y location of each chromosome spread that is detected is stored. The computer measures the chromosomes in a spread, classifies them by group or by type and also prepares a digital karyotype image. The computer system can also prepare a patient report summarizing the result of the analysis and listing suspected abnormalities.

Early detection of glaucoma using fully automated disparity analysis of the optic nerve head (ONH) from stereo fundus images

NASA Astrophysics Data System (ADS)

Sharma, Archie; Corona, Enrique; Mitra, Sunanda; Nutter, Brian S.

2006-03-01

Early detection of structural damage to the optic nerve head (ONH) is critical in diagnosis of glaucoma, because such glaucomatous damage precedes clinically identifiable visual loss. Early detection of glaucoma can prevent progression of the disease and consequent loss of vision. Traditional early detection techniques involve observing changes in the ONH through an ophthalmoscope. Stereo fundus photography is also routinely used to detect subtle changes in the ONH. However, clinical evaluation of stereo fundus photographs suffers from inter- and intra-subject variability. Even the Heidelberg Retina Tomograph (HRT) has not been found to be sufficiently sensitive for early detection. A semi-automated algorithm for quantitative representation of the optic disc and cup contours by computing accumulated disparities in the disc and cup regions from stereo fundus image pairs has already been developed using advanced digital image analysis methodologies. A 3-D visualization of the disc and cup is achieved assuming camera geometry. High correlation among computer-generated and manually segmented cup to disc ratios in a longitudinal study involving 159 stereo fundus image pairs has already been demonstrated. However, clinical usefulness of the proposed technique can only be tested by a fully automated algorithm. In this paper, we present a fully automated algorithm for segmentation of optic cup and disc contours from corresponding stereo disparity information. Because this technique does not involve human intervention, it eliminates subjective variability encountered in currently used clinical methods and provides ophthalmologists with a cost-effective and quantitative method for detection of ONH structural damage for early detection of glaucoma.

Highly Sensitive and Automated Surface Enhanced Raman Scattering-based Immunoassay for H5N1 Detection with Digital Microfluidics.

PubMed

Wang, Yang; Ruan, Qingyu; Lei, Zhi-Chao; Lin, Shui-Chao; Zhu, Zhi; Zhou, Leiji; Yang, Chaoyong

2018-04-17

Digital microfluidics (DMF) is a powerful platform for a broad range of applications, especially immunoassays having multiple steps, due to the advantages of low reagent consumption and high automatization. Surface enhanced Raman scattering (SERS) has been proven as an attractive method for highly sensitive and multiplex detection, because of its remarkable signal amplification and excellent spatial resolution. Here we propose a SERS-based immunoassay with DMF for rapid, automated, and sensitive detection of disease biomarkers. SERS tags labeled with Raman reporter 4-mercaptobenzoic acid (4-MBA) were synthesized with a core@shell nanostructure and showed strong signals, good uniformity, and high stability. A sandwich immunoassay was designed, in which magnetic beads coated with antibodies were used as solid support to capture antigens from samples to form a beads-antibody-antigen immunocomplex. By labeling the immunocomplex with a detection antibody-functionalized SERS tag, antigen can be sensitively detected through the strong SERS signal. The automation capability of DMF can greatly simplify the assay procedure while reducing the risk of exposure to hazardous samples. Quantitative detection of avian influenza virus H5N1 in buffer and human serum was implemented to demonstrate the utility of the DMF-SERS method. The DMF-SERS method shows excellent sensitivity (LOD of 74 pg/mL) and selectivity for H5N1 detection with less assay time (<1 h) and lower reagent consumption (∼30 μL) compared to the standard ELISA method. Therefore, this DMF-SERS method holds great potentials for automated and sensitive detection of a variety of infectious diseases.

High precision automated face localization in thermal images: oral cancer dataset as test case

NASA Astrophysics Data System (ADS)

Chakraborty, M.; Raman, S. K.; Mukhopadhyay, S.; Patsa, S.; Anjum, N.; Ray, J. G.

2017-02-01

Automated face detection is the pivotal step in computer vision aided facial medical diagnosis and biometrics. This paper presents an automatic, subject adaptive framework for accurate face detection in the long infrared spectrum on our database for oral cancer detection consisting of malignant, precancerous and normal subjects of varied age group. Previous works on oral cancer detection using Digital Infrared Thermal Imaging(DITI) reveals that patients and normal subjects differ significantly in their facial thermal distribution. Therefore, it is a challenging task to formulate a completely adaptive framework to veraciously localize face from such a subject specific modality. Our model consists of first extracting the most probable facial regions by minimum error thresholding followed by ingenious adaptive methods to leverage the horizontal and vertical projections of the segmented thermal image. Additionally, the model incorporates our domain knowledge of exploiting temperature difference between strategic locations of the face. To our best knowledge, this is the pioneering work on detecting faces in thermal facial images comprising both patients and normal subjects. Previous works on face detection have not specifically targeted automated medical diagnosis; face bounding box returned by those algorithms are thus loose and not apt for further medical automation. Our algorithm significantly outperforms contemporary face detection algorithms in terms of commonly used metrics for evaluating face detection accuracy. Since our method has been tested on challenging dataset consisting of both patients and normal subjects of diverse age groups, it can be seamlessly adapted in any DITI guided facial healthcare or biometric applications.

Evaluating the Advisory Flags and Machine Scoring Difficulty in the "e-rater"® Automated Scoring Engine. Research Report. ETS RR-16-30

ERIC Educational Resources Information Center

Zhang, Mo; Chen, Jing; Ruan, Chunyi

2016-01-01

Successful detection of unusual responses is critical for using machine scoring in the assessment context. This study evaluated the utility of approaches to detecting unusual responses in automated essay scoring. Two research questions were pursued. One question concerned the performance of various prescreening advisory flags, and the other…

Automated synthesis, insertion and detection of polyps for CT colonography

NASA Astrophysics Data System (ADS)

Sezille, Nicolas; Sadleir, Robert J. T.; Whelan, Paul F.

2003-03-01

CT Colonography (CTC) is a new non-invasive colon imaging technique which has the potential to replace conventional colonoscopy for colorectal cancer screening. A novel system which facilitates automated detection of colorectal polyps at CTC is introduced. As exhaustive testing of such a system using real patient data is not feasible, more complete testing is achieved through synthesis of artificial polyps and insertion into real datasets. The polyp insertion is semi-automatic: candidate points are manually selected using a custom GUI, suitable points are determined automatically from an analysis of the local neighborhood surrounding each of the candidate points. Local density and orientation information are used to generate polyps based on an elliptical model. Anomalies are identified from the modified dataset by analyzing the axial images. Detected anomalies are classified as potential polyps or natural features using 3D morphological techniques. The final results are flagged for review. The system was evaluated using 15 scenarios. The sensitivity of the system was found to be 65% with 34% false positive detections. Automated diagnosis at CTC is possible and thorough testing is facilitated by augmenting real patient data with computer generated polyps. Ultimately, automated diagnosis will enhance standard CTC and increase performance.

Automated detection of case clusters of waterborne acute gastroenteritis from health insurance data - pilot study in three French districts.

PubMed

Rambaud, Loïc; Galey, Catherine; Beaudeau, Pascal

2016-04-01

This pilot study was conducted to assess the utility of using a health insurance database for the automated detection of waterborne outbreaks of acute gastroenteritis (AGE). The weekly number of AGE cases for which the patient consulted a doctor (cAGE) was derived from this database for 1,543 towns in three French districts during the 2009-2012 period. The method we used is based on a spatial comparison of incidence rates and of their time trends between the target town and the district. Each municipality was tested, week by week, for the entire study period. Overall, 193 clusters were identified, 10% of the municipalities were involved in at least one cluster and less than 2% in several. We can infer that nationwide more than 1,000 clusters involving 30,000 cases of cAGE each year may be linked to tap water. The clusters discovered with this automated detection system will be reported to local operators for investigation of the situations at highest risk. This method will be compared with others before automated detection is implemented on a national level.

Automated mitosis detection of stem cell populations in phase-contrast microscopy images.

PubMed

Huh, Seungil; Ker, Dai Fei Elmer; Bise, Ryoma; Chen, Mei; Kanade, Takeo

2011-03-01

Due to the enormous potential and impact that stem cells may have on regenerative medicine, there has been a rapidly growing interest for tools to analyze and characterize the behaviors of these cells in vitro in an automated and high throughput fashion. Among these behaviors, mitosis, or cell division, is important since stem cells proliferate and renew themselves through mitosis. However, current automated systems for measuring cell proliferation often require destructive or sacrificial methods of cell manipulation such as cell lysis or in vitro staining. In this paper, we propose an effective approach for automated mitosis detection using phase-contrast time-lapse microscopy, which is a nondestructive imaging modality, thereby allowing continuous monitoring of cells in culture. In our approach, we present a probabilistic model for event detection, which can simultaneously 1) identify spatio-temporal patch sequences that contain a mitotic event and 2) localize a birth event, defined as the time and location at which cell division is completed and two daughter cells are born. Our approach significantly outperforms previous approaches in terms of both detection accuracy and computational efficiency, when applied to multipotent C3H10T1/2 mesenchymal and C2C12 myoblastic stem cell populations.

Automated 3D-Printed Unibody Immunoarray for Chemiluminescence Detection of Cancer Biomarker Proteins

PubMed Central

Tang, C. K.; Vaze, A.; Rusling, J. F.

2017-01-01

A low cost three-dimensional (3D) printed clear plastic microfluidic device was fabricated for fast, low cost automated protein detection. The unibody device features three reagent reservoirs, an efficient 3D network for passive mixing, and an optically transparent detection chamber housing a glass capture antibody array for measuring chemiluminescence output with a CCD camera. Sandwich type assays were built onto the glass arrays using a multi-labeled detection antibody-polyHRP (HRP = horseradish peroxidase). Total assay time was ~30 min in a complete automated assay employing a programmable syringe pump so that the protocol required minimal operator intervention. The device was used for multiplexed detection of prostate cancer biomarker proteins prostate specific antigen (PSA) and platelet factor 4 (PF-4). Detection limits of 0.5 pg mL−1 were achieved for these proteins in diluted serum with log dynamic ranges of four orders of magnitude. Good accuracy vs ELISA was validated by analyzing human serum samples. This prototype device holds good promise for further development as a point-of-care cancer diagnostics tool. PMID:28067370

Automated, per pixel Cloud Detection from High-Resolution VNIR Data

NASA Technical Reports Server (NTRS)

Varlyguin, Dmitry L.

2007-01-01

CASA is a fully automated software program for the per-pixel detection of clouds and cloud shadows from medium- (e.g., Landsat, SPOT, AWiFS) and high- (e.g., IKONOS, QuickBird, OrbView) resolution imagery without the use of thermal data. CASA is an object-based feature extraction program which utilizes a complex combination of spectral, spatial, and contextual information available in the imagery and the hierarchical self-learning logic for accurate detection of clouds and their shadows.

Detection of tumor DNA at the margins of colorectal cancer liver metastasis

PubMed Central

Holdhoff, Matthias; Schmidt, Kerstin; Diehl, Frank; Aggrawal, Nishant; Angenendt, Philipp; Romans, Katharine; Edelstein, Daniel L.; Torbenson, Michael; Kinzler, Kenneth W.; Vogelstein, Bert; Choti, Michael A.; Diaz, Luis A.

2012-01-01

Purpose Defining an adequate resection margin of colorectal cancer liver metastases is essential for optimizing surgical technique. We have attempted to evaluate the resection margin through a combination of histopathologic and genetic analyses. Experimental Design We evaluated 88 samples of tumor margins from 12 patients with metastatic colon cancer who each underwent partial hepatectomy of one to six liver metastases. Punch biopsies of surrounding liver tissue were obtained at 4, 8, 12 and 16 mm from the tumor border. DNA from these biopsies was analyzed by a sensitive PCR-based technique, called BEAMing, for mutations of KRAS, PIK3CA, APC, or TP53 identified in the corresponding tumor. Results Mutations were identified in each patient’s resected tumor and used to analyze the 88 samples circumscribing the tumor-normal border. Tumor-specific mutant DNA was detectable in surrounding liver tissue in five of these 88 samples, all within 4 mm of the tumor border. Biopsies that were 8, 12, and 16 mm from the macroscopic visible margin were devoid of detectable mutant tumor DNA as well as of microscopically visible cancer cells. Tumors with a significant radiologic response to chemotherapy were not associated with any increase in mutant tumor DNA in beyond 4 mm of the main tumor. Conclusions Mutant tumor-specific DNA can be detected beyond the visible tumor margin, but never beyond 4 mm, even in patients whose tumors were larger prior to chemotherapy. These data provide a rational basis for determining the extent of surgical excision required in patients undergoing resection of liver metastases. PMID:21531819

Automated detection of new impact sites on Martian surface from HiRISE images

NASA Astrophysics Data System (ADS)

Xin, Xin; Di, Kaichang; Wang, Yexin; Wan, Wenhui; Yue, Zongyu

2017-10-01

In this study, an automated method for Martian new impact site detection from single images is presented. It first extracts dark areas in full high resolution image, then detects new impact craters within dark areas using a cascade classifier which combines local binary pattern features and Haar-like features trained by an AdaBoost machine learning algorithm. Experimental results using 100 HiRISE images show that the overall detection rate of proposed method is 84.5%, with a true positive rate of 86.9%. The detection rate and true positive rate in the flat regions are 93.0% and 91.5%, respectively.

Systems and Methods for Automated Water Detection Using Visible Sensors

NASA Technical Reports Server (NTRS)

Rankin, Arturo L. (Inventor); Matthies, Larry H. (Inventor); Bellutta, Paolo (Inventor)

2016-01-01

Systems and methods are disclosed that include automated machine vision that can utilize images of scenes captured by a 3D imaging system configured to image light within the visible light spectrum to detect water. One embodiment includes autonomously detecting water bodies within a scene including capturing at least one 3D image of a scene using a sensor system configured to detect visible light and to measure distance from points within the scene to the sensor system, and detecting water within the scene using a processor configured to detect regions within each of the at least one 3D images that possess at least one characteristic indicative of the presence of water.

Incidence rates of hospital-acquired urinary tract and bloodstream infections generated by automated compilation of electronically available healthcare data.

PubMed

Redder, J D; Leth, R A; Møller, J K

2015-11-01

Monitoring of hospital-acquired infection (HAI) by automated compilation of registry data may address the disadvantages of laborious, costly and potentially subjective and often random sampling of data by manual surveillance. To evaluate a system for automated monitoring of hospital-acquired urinary tract (HA-UTI) and bloodstream infections (HA-BSI) and to report incidence rates over a five-year period in a Danish hospital trust. Based primarily on electronically available data relating to microbiology results and antibiotic prescriptions, the automated monitoring of HA-UTIs and HA-BSIs was validated against data from six previous point-prevalence surveys (PPS) from 2010 to 2013 and data from a manual assessment (HA-UTI only) of one department of internal medicine from January 2010. Incidence rates (infections per 1000 bed-days) from 2010 to 2014 were calculated. Compared with the PPSs, the automated monitoring showed a sensitivity of 88% in detecting UTI in general, 78% in detecting HA-UTI, and 100% in detecting BSI in general. The monthly incidence rates varied between 4.14 and 6.61 per 1000 bed-days for HA-UTI and between 0.09 and 1.25 per 1000 bed-days for HA-BSI. Replacing PPSs with automated monitoring of HAIs may provide better and more objective data and constitute a promising foundation for individual patient risk analyses and epidemiological studies. Automated monitoring may be universally applicable in hospitals with electronic databases comprising microbiological findings, admission data, and antibiotic prescriptions. Copyright © 2015 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

A longitudinal evaluation of performance of automated BCR-ABL1 quantitation using cartridge-based detection system.

PubMed

Enjeti, Anoop; Granter, Neil; Ashraf, Asma; Fletcher, Linda; Branford, Susan; Rowlings, Philip; Dooley, Susan

2015-10-01

An automated cartridge-based detection system (GeneXpert; Cepheid) is being widely adopted in low throughput laboratories for monitoring BCR-ABL1 transcript in chronic myelogenous leukaemia. This Australian study evaluated the longitudinal performance specific characteristics of the automated system.The automated cartridge-based system was compared prospectively with the manual qRT-PCR-based reference method at SA Pathology, Adelaide, over a period of 2.5 years. A conversion factor determination was followed by four re-validations. Peripheral blood samples (n = 129) with international scale (IS) values within detectable range were selected for assessment. The mean bias, proportion of results within specified fold difference (2-, 3- and 5-fold), the concordance rate of major molecular remission (MMR) and concordance across a range of IS values on paired samples were evaluated.The initial conversion factor for the automated system was determined as 0.43. Except for the second re-validation, where a negative bias of 1.9-fold was detected, all other biases fell within desirable limits. A cartridge-specific conversion factor and efficiency value was introduced and the conversion factor was confirmed to be stable in subsequent re-validation cycles. Concordance with the reference method/laboratory at >0.1-≤10 IS was 78.2% and at ≤0.001 was 80%, compared to 86.8% in the >0.01-≤0.1 IS range. The overall and MMR concordance were 85.7% and 94% respectively, for samples that fell within ± 5-fold of the reference laboratory value over the entire period of study.Conversion factor and performance specific characteristics for the automated system were longitudinally stable in the clinically relevant range, following introduction by the manufacturer of lot specific efficiency values.

Molecular assessment of artemisinin resistance markers, polymorphisms in the k13 propeller, and a multidrug-resistance gene in the eastern and western border areas of Myanmar.

PubMed

Nyunt, Myat Htut; Hlaing, Thaung; Oo, Htet Wai; Tin-Oo, Lu-Lu Kyaw; Phway, Hnin Phyu; Wang, Bo; Zaw, Ni Ni; Han, Soe Soe; Tun, Thurein; San, Kyaw Kyaw; Kyaw, Myat Phone; Han, Eun-Taek

2015-04-15

As K13 propeller mutations have been recently reported to serve as molecular markers, assessment of K13 propeller polymorphisms in multidrug-resistant gene in isolates from Myanmar, especially the eastern and western border areas, is crucial if we are to understand the spread of artemisinin resistance. A 3-day surveillance study was conducted in the eastern and western border areas in Myanmar, and K13 propeller and Plasmodium falciparum multidrug resistance-associated protein 1 (pfmrp1) mutations were analyzed. Among the 1761 suspected malaria cases screened, a total of 42 uncomplicated falciparum cases from the eastern border and 49 from the western border were subjected to 3 days of surveillance after artemether-lumefantrine treatment. No parasitemic case showing positivity on day 3 was noted from the western border, but 26.2% (11/42) of cases were positive in the eastern border. Although we found no marked difference in the prevalence of the pfmrp1 mutation in the eastern and western borders (36% vs 31%, respectively), K13 mutations were more frequent in the eastern border area (where the 3-day persistent cases were detected; 48% vs 14%). C580Y, M476I, A481V, N458Y, R539T, and R516Y accounted for 68.9% of all K13 mutations significantly associated with day 3 parasitaemia. The K13 mutations were significantly associated with day 3 parasitaemia, emphasizing the importance of K13 surveillance. The low prevalence of K13 mutations and the absence of day 3 parasitaemic cases indicate that artemisinin resistance may not have spread to the western Myanmar border region. Although analysis of multiple K13 mutations is challenging, it should be done at various sentinel sites in Myanmar. © The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Method and automated apparatus for detecting coliform organisms

NASA Technical Reports Server (NTRS)

Dill, W. P.; Taylor, R. E.; Jeffers, E. L. (Inventor)

1980-01-01

Method and automated apparatus are disclosed for determining the time of detection of metabolically produced hydrogen by coliform bacteria cultured in an electroanalytical cell from the time the cell is inoculated with the bacteria. The detection time data provides bacteria concentration values. The apparatus is sequenced and controlled by a digital computer to discharge a spent sample, clean and sterilize the culture cell, provide a bacteria nutrient into the cell, control the temperature of the nutrient, inoculate the nutrient with a bacteria sample, measures the electrical potential difference produced by the cell, and measures the time of detection from inoculation.

Automated macromolecular crystal detection system and method

DOEpatents

Christian, Allen T [Tracy, CA; Segelke, Brent [San Ramon, CA; Rupp, Bernard [Livermore, CA; Toppani, Dominique [Fontainebleau, FR

2007-06-05

An automated macromolecular method and system for detecting crystals in two-dimensional images, such as light microscopy images obtained from an array of crystallization screens. Edges are detected from the images by identifying local maxima of a phase congruency-based function associated with each image. The detected edges are segmented into discrete line segments, which are subsequently geometrically evaluated with respect to each other to identify any crystal-like qualities such as, for example, parallel lines, facing each other, similarity in length, and relative proximity. And from the evaluation a determination is made as to whether crystals are present in each image.

TeraSCREEN: multi-frequency multi-mode Terahertz screening for border checks

NASA Astrophysics Data System (ADS)

Alexander, Naomi E.; Alderman, Byron; Allona, Fernando; Frijlink, Peter; Gonzalo, Ramón; Hägelen, Manfred; Ibáñez, Asier; Krozer, Viktor; Langford, Marian L.; Limiti, Ernesto; Platt, Duncan; Schikora, Marek; Wang, Hui; Weber, Marc Andree

2014-06-01

The challenge for any security screening system is to identify potentially harmful objects such as weapons and explosives concealed under clothing. Classical border and security checkpoints are no longer capable of fulfilling the demands of today's ever growing security requirements, especially with respect to the high throughput generally required which entails a high detection rate of threat material and a low false alarm rate. TeraSCREEN proposes to develop an innovative concept of multi-frequency multi-mode Terahertz and millimeter-wave detection with new automatic detection and classification functionalities. The system developed will demonstrate, at a live control point, the safe automatic detection and classification of objects concealed under clothing, whilst respecting privacy and increasing current throughput rates. This innovative screening system will combine multi-frequency, multi-mode images taken by passive and active subsystems which will scan the subjects and obtain complementary spatial and spectral information, thus allowing for automatic threat recognition. The TeraSCREEN project, which will run from 2013 to 2016, has received funding from the European Union's Seventh Framework Programme under the Security Call. This paper will describe the project objectives and approach.

Automatic detection of retina disease: robustness to image quality and localization of anatomy structure.

PubMed

Karnowski, T P; Aykac, D; Giancardo, L; Li, Y; Nichols, T; Tobin, K W; Chaum, E

2011-01-01

The automated detection of diabetic retinopathy and other eye diseases in images of the retina has great promise as a low-cost method for broad-based screening. Many systems in the literature which perform automated detection include a quality estimation step and physiological feature detection, including the vascular tree and the optic nerve / macula location. In this work, we study the robustness of an automated disease detection method with respect to the accuracy of the optic nerve location and the quality of the images obtained as judged by a quality estimation algorithm. The detection algorithm features microaneurysm and exudate detection followed by feature extraction on the detected population to describe the overall retina image. Labeled images of retinas ground-truthed to disease states are used to train a supervised learning algorithm to identify the disease state of the retina image and exam set. Under the restrictions of high confidence optic nerve detections and good quality imagery, the system achieves a sensitivity and specificity of 94.8% and 78.7% with area-under-curve of 95.3%. Analysis of the effect of constraining quality and the distinction between mild non-proliferative diabetic retinopathy, normal retina images, and more severe disease states is included.

Automatic CDR Estimation for Early Glaucoma Diagnosis

PubMed Central

Sarmiento, A.; Sanchez-Morillo, D.; Jiménez, S.; Alemany, P.

2017-01-01

Glaucoma is a degenerative disease that constitutes the second cause of blindness in developed countries. Although it cannot be cured, its progression can be prevented through early diagnosis. In this paper, we propose a new algorithm for automatic glaucoma diagnosis based on retinal colour images. We focus on capturing the inherent colour changes of optic disc (OD) and cup borders by computing several colour derivatives in CIE L∗a∗b∗ colour space with CIE94 colour distance. In addition, we consider spatial information retaining these colour derivatives and the original CIE L∗a∗b∗ values of the pixel and adding other characteristics such as its distance to the OD centre. The proposed strategy is robust due to a simple structure that does not need neither initial segmentation nor removal of the vascular tree or detection of vessel bends. The method has been extensively validated with two datasets (one public and one private), each one comprising 60 images of high variability of appearances. Achieved class-wise-averaged accuracy of 95.02% and 81.19% demonstrates that this automated approach could support physicians in the diagnosis of glaucoma in its early stage, and therefore, it could be seen as an opportunity for developing low-cost solutions for mass screening programs. PMID:29279773

Automated Eddy Current Inspection on Space Shuttle Hardware

NASA Technical Reports Server (NTRS)

Hartmann, John; Felker, Jeremy

2007-01-01

Over the life time of the Space Shuttle program, metal parts used for the Reusable Solid Rocket Motors (RSRMs) have been nondestructively inspected for cracks and surface breaking discontinuities using magnetic particle (steel) and penetrant methods. Although these inspections adequately screened for critical sized cracks in most regions of the hardware, it became apparent after detection of several sub-critical flaws that the processes were very dependent on operator attentiveness and training. Throughout the 1990's, eddy current inspections were added to areas that had either limited visual access or were more fracture critical. In the late 1990's. a project was initiated to upgrade NDE inspections with the overall objective of improving inspection reliability and control. An automated eddy current inspection system was installed in 2001. A figure shows one of the inspection bays with the robotic axis of the system highlighted. The system was programmed to inspect the various case, nozzle, and igniter metal components that make up an RSRM. both steel and aluminum. For the past few years, the automated inspection system has been a part of the baseline inspection process for steel components. Although the majority of the RSRM metal part inventory ts free of detectable surface flaws, a few small, sub-critical manufacturing defects have been detected with the automated system. This paper will summarize the benefits that have been realized with the current automated eddy current system, as well as the flaws that have been detected.

Automation in visual inspection tasks: X-ray luggage screening supported by a system of direct, indirect or adaptable cueing with low and high system reliability.

PubMed

Chavaillaz, Alain; Schwaninger, Adrian; Michel, Stefan; Sauer, Juergen

2018-05-25

The present study evaluated three automation modes for improving performance in an X-ray luggage screening task. 140 participants were asked to detect the presence of prohibited items in X-ray images of cabin luggage. Twenty participants conducted this task without automatic support (control group), whereas the others worked with either indirect cues (system indicated the target presence without specifying its location), or direct cues (system pointed out the exact target location) or adaptable automation (participants could freely choose between no cue, direct and indirect cues). Furthermore, automatic support reliability was manipulated (low vs. high). The results showed a clear advantage for direct cues regarding detection performance and response time. No benefits were observed for adaptable automation. Finally, high automation reliability led to better performance and higher operator trust. The findings overall confirmed that automatic support systems for luggage screening should be designed such that they provide direct, highly reliable cues.

Signal amplification of FISH for automated detection using image cytometry.

PubMed

Truong, K; Boenders, J; Maciorowski, Z; Vielh, P; Dutrillaux, B; Malfoy, B; Bourgeois, C A

1997-05-01

The purpose of this study was to improve the detection of FISH signals, in order that spot counting by a fully automated image cytometer be comparable to that obtained visually under the microscope. Two systems of spot scoring, visual and automated counting, were investigated in parallel on stimulated human lymphocytes with FISH using a biotinylated centromeric probe for chromosome 3. Signal characteristics were first analyzed on images recorded with a coupled charge device (CCD) camera. Number of spots per nucleus were scored visually on these recorded images versus automatically with a DISCOVERY image analyzer. Several fluochromes, amplification and pretreatments were tested. Our results for both visual and automated scoring show that the tyramide amplification system (TSA) gives the best amplification of signal if pepsin treatment is applied prior to FISH. Accuracy of the automated scoring, however, remained low (58% of nuclei containing two spots) compared to the visual scoring because of the high intranuclear variation between FISH spots.

Automated Detection and Classification in High-Resolution Sonar Imagery for Autonomous Underwater Vehicle Operations

DTIC Science & Technology

2008-12-01

n. , ’>, ,. Australian Government Department of Defence Defence Science and Technology Organisation Automated Detection and Classification in... Organisation DSTO-GD-0537 ABSTRACT Autonomous Underwater Vehicles (AUVs) are increasingly being used by military forces to acquire high-resolution sonar...release Published by Maritime Operations Division DsTO Defrnce sdence and Technology Organisation PO Box 1500 Edinburgh South Australia 5111 Australia

Automated Detection of Solar Loops by the Oriented Connectivity Method

NASA Technical Reports Server (NTRS)

Lee, Jong Kwan; Newman, Timothy S.; Gary, G. Allen

2004-01-01

An automated technique to segment solar coronal loops from intensity images of the Sun s corona is introduced. It exploits physical characteristics of the solar magnetic field to enable robust extraction from noisy images. The technique is a constructive curve detection approach, constrained by collections of estimates of the magnetic fields orientation. Its effectiveness is evaluated through experiments on synthetic and real coronal images.

CT imaging spectrum of infiltrative renal diseases.

PubMed

Ballard, David H; De Alba, Luis; Migliaro, Matias; Previgliano, Carlos H; Sangster, Guillermo P

2017-11-01

Most renal lesions replace the renal parenchyma as a focal space-occupying mass with borders distinguishing the mass from normal parenchyma. However, some renal lesions exhibit interstitial infiltration-a process that permeates the renal parenchyma by using the normal renal architecture for growth. These infiltrative lesions frequently show nonspecific patterns that lead to little or no contour deformity and have ill-defined borders on CT, making detection and diagnosis challenging. The purpose of this pictorial essay is to describe the CT imaging findings of various conditions that may manifest as infiltrative renal lesions.

SU-G-201-03: Automation of High Dose Rate Brachytherapy Quality Assurance: Development of a Radioluminescent Detection System for Simultaneous Detection of Activity, Timing, and Positioning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jenkins, C; Xing, L; Fahimian, B

Purpose: Accuracy of positioning, timing and activity is of critical importance for High Dose Rate (HDR) brachytherapy delivery. Respective measurements via film autoradiography, stop-watches and well chambers can be cumbersome, crude or lack dynamic source evaluation capabilities. To address such limitations, a single device radioluminescent detection system enabling automated real-time quantification of activity, position and timing accuracy is presented and experimentally evaluated. Methods: A radioluminescent sheet was fabricated by mixing Gd?O?S:Tb with PDMS and incorporated into a 3D printed device where it was fixated below a CMOS digital camera. An Ir-192 HDR source (VS2000, VariSource iX) with an effective activemore » length of 5 mm was introduced using a 17-gauge stainless steel needle below the sheet. Pixel intensity values for determining activity were taken from an ROI centered on the source location. A calibration curve relating intensity values to activity was generated and used to evaluate automated activity determination with data gathered over 6 weeks. Positioning measurements were performed by integrating images for an entire delivery and fitting peaks to the resulting profile. Timing measurements were performed by evaluating source location and timestamps from individual images. Results: Average predicted activity error over 6 weeks was .35 ± .5%. The distance between four dwell positions was determined by the automated system to be 1.99 ± .02 cm. The result from autoradiography was 2.00 ± .03 cm. The system achieved a time resolution of 10 msec and determined the dwell time to be 1.01 sec ± .02 sec. Conclusion: The system was able to successfully perform automated detection of activity, positioning and timing concurrently under a single setup. Relative to radiochromic and radiographic film-based autoradiography, which can only provide a static evaluation positioning, optical detection of temporary radiation induced luminescence enables dynamic detection of position enabling automated quantification of timing with millisecond accuracy.« less

Automated detection of analyzable metaphase chromosome cells depicted on scanned digital microscopic images

NASA Astrophysics Data System (ADS)

Qiu, Yuchen; Wang, Xingwei; Chen, Xiaodong; Li, Yuhua; Liu, Hong; Li, Shibo; Zheng, Bin

2010-02-01

Visually searching for analyzable metaphase chromosome cells under microscopes is quite time-consuming and difficult. To improve detection efficiency, consistency, and diagnostic accuracy, an automated microscopic image scanning system was developed and tested to directly acquire digital images with sufficient spatial resolution for clinical diagnosis. A computer-aided detection (CAD) scheme was also developed and integrated into the image scanning system to search for and detect the regions of interest (ROI) that contain analyzable metaphase chromosome cells in the large volume of scanned images acquired from one specimen. Thus, the cytogeneticists only need to observe and interpret the limited number of ROIs. In this study, the high-resolution microscopic image scanning and CAD performance was investigated and evaluated using nine sets of images scanned from either bone marrow (three) or blood (six) specimens for diagnosis of leukemia. The automated CAD-selection results were compared with the visual selection. In the experiment, the cytogeneticists first visually searched for the analyzable metaphase chromosome cells from specimens under microscopes. The specimens were also automated scanned and followed by applying the CAD scheme to detect and save ROIs containing analyzable cells while deleting the others. The automated selected ROIs were then examined by a panel of three cytogeneticists. From the scanned images, CAD selected more analyzable cells than initially visual examinations of the cytogeneticists in both blood and bone marrow specimens. In general, CAD had higher performance in analyzing blood specimens. Even in three bone marrow specimens, CAD selected 50, 22, 9 ROIs, respectively. Except matching with the initially visual selection of 9, 7, and 5 analyzable cells in these three specimens, the cytogeneticists also selected 41, 15 and 4 new analyzable cells, which were missed in initially visual searching. This experiment showed the feasibility of applying this CAD-guided high-resolution microscopic image scanning system to prescreen and select ROIs that may contain analyzable metaphase chromosome cells. The success and the further improvement of this automated scanning system may have great impact on the future clinical practice in genetic laboratories to detect and diagnose diseases.

Automated Image Analysis Corrosion Working Group Update: February 1, 2018

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wendelberger, James G.

These are slides for the automated image analysis corrosion working group update. The overall goals were: automate the detection and quantification of features in images (faster, more accurate), how to do this (obtain data, analyze data), focus on Laser Scanning Confocal Microscope (LCM) data (laser intensity, laser height/depth, optical RGB, optical plus laser RGB).

Open-source software for collision detection in external beam radiation therapy

NASA Astrophysics Data System (ADS)

Suriyakumar, Vinith M.; Xu, Renee; Pinter, Csaba; Fichtinger, Gabor

2017-03-01

PURPOSE: Collision detection for external beam radiation therapy (RT) is important for eliminating the need for dryruns that aim to ensure patient safety. Commercial treatment planning systems (TPS) offer this feature but they are expensive and proprietary. Cobalt-60 RT machines are a viable solution to RT practice in low-budget scenarios. However, such clinics are hesitant to invest in these machines due to a lack of affordable treatment planning software. We propose the creation of an open-source room's eye view visualization module with automated collision detection as part of the development of an open-source TPS. METHODS: An openly accessible linac 3D geometry model is sliced into the different components of the treatment machine. The model's movements are based on the International Electrotechnical Commission standard. Automated collision detection is implemented between the treatment machine's components. RESULTS: The room's eye view module was built in C++ as part of SlicerRT, an RT research toolkit built on 3D Slicer. The module was tested using head and neck and prostate RT plans. These tests verified that the module accurately modeled the movements of the treatment machine and radiation beam. Automated collision detection was verified using tests where geometric parameters of the machine's components were changed, demonstrating accurate collision detection. CONCLUSION: Room's eye view visualization and automated collision detection are essential in a Cobalt-60 treatment planning system. Development of these features will advance the creation of an open-source TPS that will potentially help increase the feasibility of adopting Cobalt-60 RT.

Effects of response bias and judgment framing on operator use of an automated aid in a target detection task.

PubMed

Rice, Stephen; McCarley, Jason S

2011-12-01

Automated diagnostic aids prone to false alarms often produce poorer human performance in signal detection tasks than equally reliable miss-prone aids. However, it is not yet clear whether this is attributable to differences in the perceptual salience of the automated aids' misses and false alarms or is the result of inherent differences in operators' cognitive responses to different forms of automation error. The present experiments therefore examined the effects of automation false alarms and misses on human performance under conditions in which the different forms of error were matched in their perceptual characteristics. Young adult participants performed a simulated baggage x-ray screening task while assisted by an automated diagnostic aid. Judgments from the aid were rendered as text messages presented at the onset of each trial, and every trial was followed by a second text message providing response feedback. Thus, misses and false alarms from the aid were matched for their perceptual salience. Experiment 1 found that even under these conditions, false alarms from the aid produced poorer human performance and engendered lower automation use than misses from the aid. Experiment 2, however, found that the asymmetry between misses and false alarms was reduced when the aid's false alarms were framed as neutral messages rather than explicit misjudgments. Results suggest that automation false alarms and misses differ in their inherent cognitive salience and imply that changes in diagnosis framing may allow designers to encourage better use of imperfectly reliable automated aids.

Radiation Detection for Homeland Security Applications

NASA Astrophysics Data System (ADS)

Ely, James

2008-05-01

In the past twenty years or so, there have been significant changes in the strategy and applications for homeland security. Recently there have been significant at deterring and interdicting terrorists and associated organizations. This is a shift in the normal paradigm of deterrence and surveillance of a nation and the `conventional' methods of warfare to the `unconventional' means that terrorist organizations resort to. With that shift comes the responsibility to monitor international borders for weapons of mass destruction, including radiological weapons. As a result, countries around the world are deploying radiation detection instrumentation to interdict the illegal shipment of radioactive material crossing international borders. These efforts include deployments at land, rail, air, and sea ports of entry in the US and in European and Asian countries. Radioactive signatures of concern include radiation dispersal devices (RDD), nuclear warheads, and special nuclear material (SNM). Radiation portal monitors (RPMs) are used as the main screening tool for vehicles and cargo at borders, supplemented by handheld detectors, personal radiation detectors, and x-ray imaging systems. This talk will present an overview of radiation detection equipment with emphasis on radiation portal monitors. In the US, the deployment of radiation detection equipment is being coordinated by the Domestic Nuclear Detection Office within the Department of Homeland Security, and a brief summary of the program will be covered. Challenges with current generation systems will be discussed as well as areas of investigation and opportunities for improvements. The next generation of radiation portal monitors is being produced under the Advanced Spectroscopic Portal program and will be available for deployment in the near future. Additional technologies, from commercially available to experimental, that provide additional information for radiation screening, such as density imaging equipment, will be reviewed. Opportunities for further research and development to improve the current equipment and methodologies for radiation detection for the important task of homeland security will be the final topic to be discussed.

Automation of diagnostic genetic testing: mutation detection by cyclic minisequencing.

PubMed

Alagrund, Katariina; Orpana, Arto K

2014-01-01

The rising role of nucleic acid testing in clinical decision making is creating a need for efficient and automated diagnostic nucleic acid test platforms. Clinical use of nucleic acid testing sets demands for shorter turnaround times (TATs), lower production costs and robust, reliable methods that can easily adopt new test panels and is able to run rare tests in random access principle. Here we present a novel home-brew laboratory automation platform for diagnostic mutation testing. This platform is based on the cyclic minisequecing (cMS) and two color near-infrared (NIR) detection. Pipetting is automated using Tecan Freedom EVO pipetting robots and all assays are performed in 384-well micro plate format. The automation platform includes a data processing system, controlling all procedures, and automated patient result reporting to the hospital information system. We have found automated cMS a reliable, inexpensive and robust method for nucleic acid testing for a wide variety of diagnostic tests. The platform is currently in clinical use for over 80 mutations or polymorphisms. Additionally to tests performed from blood samples, the system performs also epigenetic test for the methylation of the MGMT gene promoter, and companion diagnostic tests for analysis of KRAS and BRAF gene mutations from formalin fixed and paraffin embedded tumor samples. Automation of genetic test reporting is found reliable and efficient decreasing the work load of academic personnel.

Chest wall segmentation in automated 3D breast ultrasound scans.

PubMed

Tan, Tao; Platel, Bram; Mann, Ritse M; Huisman, Henkjan; Karssemeijer, Nico

2013-12-01

In this paper, we present an automatic method to segment the chest wall in automated 3D breast ultrasound images. Determining the location of the chest wall in automated 3D breast ultrasound images is necessary in computer-aided detection systems to remove automatically detected cancer candidates beyond the chest wall and it can be of great help for inter- and intra-modal image registration. We show that the visible part of the chest wall in an automated 3D breast ultrasound image can be accurately modeled by a cylinder. We fit the surface of our cylinder model to a set of automatically detected rib-surface points. The detection of the rib-surface points is done by a classifier using features representing local image intensity patterns and presence of rib shadows. Due to attenuation of the ultrasound signal, a clear shadow is visible behind the ribs. Evaluation of our segmentation method is done by computing the distance of manually annotated rib points to the surface of the automatically detected chest wall. We examined the performance on images obtained with the two most common 3D breast ultrasound devices in the market. In a dataset of 142 images, the average mean distance of the annotated points to the segmented chest wall was 5.59 ± 3.08 mm. Copyright © 2012 Elsevier B.V. All rights reserved.

Automated detection and enumeration of marine wildlife using unmanned aircraft systems (UAS) and thermal imagery

PubMed Central

Seymour, A. C.; Dale, J.; Hammill, M.; Halpin, P. N.; Johnston, D. W.

2017-01-01

Estimating animal populations is critical for wildlife management. Aerial surveys are used for generating population estimates, but can be hampered by cost, logistical complexity, and human risk. Additionally, human counts of organisms in aerial imagery can be tedious and subjective. Automated approaches show promise, but can be constrained by long setup times and difficulty discriminating animals in aggregations. We combine unmanned aircraft systems (UAS), thermal imagery and computer vision to improve traditional wildlife survey methods. During spring 2015, we flew fixed-wing UAS equipped with thermal sensors, imaging two grey seal (Halichoerus grypus) breeding colonies in eastern Canada. Human analysts counted and classified individual seals in imagery manually. Concurrently, an automated classification and detection algorithm discriminated seals based upon temperature, size, and shape of thermal signatures. Automated counts were within 95–98% of human estimates; at Saddle Island, the model estimated 894 seals compared to analyst counts of 913, and at Hay Island estimated 2188 seals compared to analysts’ 2311. The algorithm improves upon shortcomings of computer vision by effectively recognizing seals in aggregations while keeping model setup time minimal. Our study illustrates how UAS, thermal imagery, and automated detection can be combined to efficiently collect population data critical to wildlife management. PMID:28338047

Automated detection and enumeration of marine wildlife using unmanned aircraft systems (UAS) and thermal imagery

NASA Astrophysics Data System (ADS)

Seymour, A. C.; Dale, J.; Hammill, M.; Halpin, P. N.; Johnston, D. W.

2017-03-01

Estimating animal populations is critical for wildlife management. Aerial surveys are used for generating population estimates, but can be hampered by cost, logistical complexity, and human risk. Additionally, human counts of organisms in aerial imagery can be tedious and subjective. Automated approaches show promise, but can be constrained by long setup times and difficulty discriminating animals in aggregations. We combine unmanned aircraft systems (UAS), thermal imagery and computer vision to improve traditional wildlife survey methods. During spring 2015, we flew fixed-wing UAS equipped with thermal sensors, imaging two grey seal (Halichoerus grypus) breeding colonies in eastern Canada. Human analysts counted and classified individual seals in imagery manually. Concurrently, an automated classification and detection algorithm discriminated seals based upon temperature, size, and shape of thermal signatures. Automated counts were within 95-98% of human estimates; at Saddle Island, the model estimated 894 seals compared to analyst counts of 913, and at Hay Island estimated 2188 seals compared to analysts’ 2311. The algorithm improves upon shortcomings of computer vision by effectively recognizing seals in aggregations while keeping model setup time minimal. Our study illustrates how UAS, thermal imagery, and automated detection can be combined to efficiently collect population data critical to wildlife management.

Automated gas chromatography

DOEpatents

Mowry, C.D.; Blair, D.S.; Rodacy, P.J.; Reber, S.D.

1999-07-13

An apparatus and process for the continuous, near real-time monitoring of low-level concentrations of organic compounds in a liquid, and, more particularly, a water stream. A small liquid volume of flow from a liquid process stream containing organic compounds is diverted by an automated process to a heated vaporization capillary where the liquid volume is vaporized to a gas that flows to an automated gas chromatograph separation column to chromatographically separate the organic compounds. Organic compounds are detected and the information transmitted to a control system for use in process control. Concentrations of organic compounds less than one part per million are detected in less than one minute. 7 figs.

PleurAlert: an augmented chest drainage system with electronic sensing, automated alerts and internet connectivity.

PubMed

Leeson, Cory E; Weaver, Robert A; Bissell, Taylor; Hoyer, Rachel; McClain, Corinne; Nelson, Douglas A; Samosky, Joseph T

2012-01-01

We have enhanced a common medical device, the chest tube drainage container, with electronic sensing of fluid volume, automated detection of critical alarm conditions and the ability to automatically send alert text messages to a nurse's cell phone. The PleurAlert system provides a simple touch-screen interface and can graphically display chest tube output over time. Our design augments a device whose basic function dates back 50 years by adding technology to automate and optimize a monitoring process that can be time consuming and inconvenient for nurses. The system may also enhance detection of emergency conditions and speed response time.

Automated gas chromatography

DOEpatents

Mowry, Curtis D.; Blair, Dianna S.; Rodacy, Philip J.; Reber, Stephen D.

1999-01-01

An apparatus and process for the continuous, near real-time monitoring of low-level concentrations of organic compounds in a liquid, and, more particularly, a water stream. A small liquid volume of flow from a liquid process stream containing organic compounds is diverted by an automated process to a heated vaporization capillary where the liquid volume is vaporized to a gas that flows to an automated gas chromatograph separation column to chromatographically separate the organic compounds. Organic compounds are detected and the information transmitted to a control system for use in process control. Concentrations of organic compounds less than one part per million are detected in less than one minute.

Migrant deaths at the Arizona-Mexico border: Spatial trends of a mass disaster.

PubMed

Giordano, Alberto; Spradley, M Katherine

2017-11-01

Geographic Information Science (GIScience) technology has been used to document, investigate, and predict patterns that may be of utility in both forensic academic research and applied practice. In examining spatial and temporal trends of the mass disaster that is occurring along the U.S.-Mexico border, other researchers have highlighted predictive patterns for search and recovery efforts as well as water station placement. The purpose of this paper is to use previously collected spatial data of migrant deaths from Arizona to address issues of data uncertainty and data accuracy that affect our understanding of this phenomenon, including local and federal policies that impact the U.S.-Mexico border. The main objective of our study was to explore how the locations of migrant deaths have varied over time. Our results confirm patterns such as a lack of relationship between Border Patrol apprehensions and migrant deaths, as well as highlight new patterns such as the increased positional accuracy of migrant deaths recorded closer to the border. This paper highlights the importance of using positionally accurate data to detect spatio-temporal trends in forensic investigations of mass disasters: without qualitative and quantitative information concerning the accuracy of the data collected, the reliability of the results obtained remains questionable. We conclude by providing a set of guidelines for standardizing the collection and documentation of migrant remains at the U.S.-Mexico border. Copyright © 2017 Elsevier B.V. All rights reserved.

Generation of stable lipid raft microdomains in the enterocyte brush border by selective endocytic removal of non-raft membrane.

PubMed

Danielsen, E Michael; Hansen, Gert H

2013-01-01

The small intestinal brush border has an unusually high proportion of glycolipids which promote the formation of lipid raft microdomains, stabilized by various cross-linking lectins. This unique membrane organization acts to provide physical and chemical stability to the membrane that faces multiple deleterious agents present in the gut lumen, such as bile salts, digestive enzymes of the pancreas, and a plethora of pathogens. In the present work, we studied the constitutive endocytosis from the brush border of cultured jejunal explants of the pig, and the results indicate that this process functions to enrich the contents of lipid raft components in the brush border. The lipophilic fluorescent marker FM, taken up into early endosomes in the terminal web region (TWEEs), was absent from detergent resistant membranes (DRMs), implying an association with non-raft membrane. Furthermore, neither major lipid raft-associated brush border enzymes nor glycolipids were detected by immunofluorescence microscopy in subapical punctae resembling TWEEs. Finally, two model raft lipids, BODIPY-lactosylceramide and BODIPY-GM1, were not endocytosed except when cholera toxin subunit B (CTB) was present. In conclusion, we propose that constitutive, selective endocytic removal of non-raft membrane acts as a sorting mechanism to enrich the brush border contents of lipid raft components, such as glycolipids and the major digestive enzymes. This sorting may be energetically driven by changes in membrane curvature when molecules move from a microvillar surface to an endocytic invagination.

Costs and consequences of automated algorithms versus manual grading for the detection of referable diabetic retinopathy.

PubMed

Scotland, G S; McNamee, P; Fleming, A D; Goatman, K A; Philip, S; Prescott, G J; Sharp, P F; Williams, G J; Wykes, W; Leese, G P; Olson, J A

2010-06-01

To assess the cost-effectiveness of an improved automated grading algorithm for diabetic retinopathy against a previously described algorithm, and in comparison with manual grading. Efficacy of the alternative algorithms was assessed using a reference graded set of images from three screening centres in Scotland (1253 cases with observable/referable retinopathy and 6333 individuals with mild or no retinopathy). Screening outcomes and grading and diagnosis costs were modelled for a cohort of 180 000 people, with prevalence of referable retinopathy at 4%. Algorithm (b), which combines image quality assessment with detection algorithms for microaneurysms (MA), blot haemorrhages and exudates, was compared with a simpler algorithm (a) (using image quality assessment and MA/dot haemorrhage (DH) detection), and the current practice of manual grading. Compared with algorithm (a), algorithm (b) would identify an additional 113 cases of referable retinopathy for an incremental cost of pound 68 per additional case. Compared with manual grading, automated grading would be expected to identify between 54 and 123 fewer referable cases, for a grading cost saving between pound 3834 and pound 1727 per case missed. Extrapolation modelling over a 20-year time horizon suggests manual grading would cost between pound 25,676 and pound 267,115 per additional quality adjusted life year gained. Algorithm (b) is more cost-effective than the algorithm based on quality assessment and MA/DH detection. With respect to the value of introducing automated detection systems into screening programmes, automated grading operates within the recommended national standards in Scotland and is likely to be considered a cost-effective alternative to manual disease/no disease grading.

Designing and evaluating an automated system for real-time medication administration error detection in a neonatal intensive care unit.

PubMed

Ni, Yizhao; Lingren, Todd; Hall, Eric S; Leonard, Matthew; Melton, Kristin; Kirkendall, Eric S

2018-05-01

Timely identification of medication administration errors (MAEs) promises great benefits for mitigating medication errors and associated harm. Despite previous efforts utilizing computerized methods to monitor medication errors, sustaining effective and accurate detection of MAEs remains challenging. In this study, we developed a real-time MAE detection system and evaluated its performance prior to system integration into institutional workflows. Our prospective observational study included automated MAE detection of 10 high-risk medications and fluids for patients admitted to the neonatal intensive care unit at Cincinnati Children's Hospital Medical Center during a 4-month period. The automated system extracted real-time medication use information from the institutional electronic health records and identified MAEs using logic-based rules and natural language processing techniques. The MAE summary was delivered via a real-time messaging platform to promote reduction of patient exposure to potential harm. System performance was validated using a physician-generated gold standard of MAE events, and results were compared with those of current practice (incident reporting and trigger tools). Physicians identified 116 MAEs from 10 104 medication administrations during the study period. Compared to current practice, the sensitivity with automated MAE detection was improved significantly from 4.3% to 85.3% (P = .009), with a positive predictive value of 78.0%. Furthermore, the system showed potential to reduce patient exposure to harm, from 256 min to 35 min (P < .001). The automated system demonstrated improved capacity for identifying MAEs while guarding against alert fatigue. It also showed promise for reducing patient exposure to potential harm following MAE events.

A self-adapting system for the automated detection of inter-ictal epileptiform discharges.

PubMed

Lodder, Shaun S; van Putten, Michel J A M

2014-01-01

Scalp EEG remains the standard clinical procedure for the diagnosis of epilepsy. Manual detection of inter-ictal epileptiform discharges (IEDs) is slow and cumbersome, and few automated methods are used to assist in practice. This is mostly due to low sensitivities, high false positive rates, or a lack of trust in the automated method. In this study we aim to find a solution that will make computer assisted detection more efficient than conventional methods, while preserving the detection certainty of a manual search. Our solution consists of two phases. First, a detection phase finds all events similar to epileptiform activity by using a large database of template waveforms. Individual template detections are combined to form "IED nominations", each with a corresponding certainty value based on the reliability of their contributing templates. The second phase uses the ten nominations with highest certainty and presents them to the reviewer one by one for confirmation. Confirmations are used to update certainty values of the remaining nominations, and another iteration is performed where ten nominations with the highest certainty are presented. This continues until the reviewer is satisfied with what has been seen. Reviewer feedback is also used to update template accuracies globally and improve future detections. Using the described method and fifteen evaluation EEGs (241 IEDs), one third of all inter-ictal events were shown after one iteration, half after two iterations, and 74%, 90%, and 95% after 5, 10 and 15 iterations respectively. Reviewing fifteen iterations for the 20-30 min recordings 1 took approximately 5 min. The proposed method shows a practical approach for combining automated detection with visual searching for inter-ictal epileptiform activity. Further evaluation is needed to verify its clinical feasibility and measure the added value it presents.

Automated indirect immunofluorescence evaluation of antinuclear autoantibodies on HEp-2 cells.

PubMed

Voigt, Jörn; Krause, Christopher; Rohwäder, Edda; Saschenbrecker, Sandra; Hahn, Melanie; Danckwardt, Maick; Feirer, Christian; Ens, Konstantin; Fechner, Kai; Barth, Erhardt; Martinetz, Thomas; Stöcker, Winfried

2012-01-01

Indirect immunofluorescence (IIF) on human epithelial (HEp-2) cells is considered as the gold standard screening method for the detection of antinuclear autoantibodies (ANA). However, in terms of automation and standardization, it has not been able to keep pace with most other analytical techniques used in diagnostic laboratories. Although there are already some automation solutions for IIF incubation in the market, the automation of result evaluation is still in its infancy. Therefore, the EUROPattern Suite has been developed as a comprehensive automated processing and interpretation system for standardized and efficient ANA detection by HEp-2 cell-based IIF. In this study, the automated pattern recognition was compared to conventional visual interpretation in a total of 351 sera. In the discrimination of positive from negative samples, concordant results between visual and automated evaluation were obtained for 349 sera (99.4%, kappa = 0.984). The system missed out none of the 272 antibody-positive samples and identified 77 out of 79 visually negative samples (analytical sensitivity/specificity: 100%/97.5%). Moreover, 94.0% of all main antibody patterns were recognized correctly by the software. Owing to its performance characteristics, EUROPattern enables fast, objective, and economic IIF ANA analysis and has the potential to reduce intra- and interlaboratory variability.

Automated Indirect Immunofluorescence Evaluation of Antinuclear Autoantibodies on HEp-2 Cells

PubMed Central

Voigt, Jörn; Krause, Christopher; Rohwäder, Edda; Saschenbrecker, Sandra; Hahn, Melanie; Danckwardt, Maick; Feirer, Christian; Ens, Konstantin; Fechner, Kai; Barth, Erhardt; Martinetz, Thomas; Stöcker, Winfried

2012-01-01

Indirect immunofluorescence (IIF) on human epithelial (HEp-2) cells is considered as the gold standard screening method for the detection of antinuclear autoantibodies (ANA). However, in terms of automation and standardization, it has not been able to keep pace with most other analytical techniques used in diagnostic laboratories. Although there are already some automation solutions for IIF incubation in the market, the automation of result evaluation is still in its infancy. Therefore, the EUROPattern Suite has been developed as a comprehensive automated processing and interpretation system for standardized and efficient ANA detection by HEp-2 cell-based IIF. In this study, the automated pattern recognition was compared to conventional visual interpretation in a total of 351 sera. In the discrimination of positive from negative samples, concordant results between visual and automated evaluation were obtained for 349 sera (99.4%, kappa = 0.984). The system missed out none of the 272 antibody-positive samples and identified 77 out of 79 visually negative samples (analytical sensitivity/specificity: 100%/97.5%). Moreover, 94.0% of all main antibody patterns were recognized correctly by the software. Owing to its performance characteristics, EUROPattern enables fast, objective, and economic IIF ANA analysis and has the potential to reduce intra- and interlaboratory variability. PMID:23251220

An automated optofluidic biosensor platform combining interferometric sensors and injection moulded microfluidics.

PubMed

Szydzik, C; Gavela, A F; Herranz, S; Roccisano, J; Knoerzer, M; Thurgood, P; Khoshmanesh, K; Mitchell, A; Lechuga, L M

2017-08-08

A primary limitation preventing practical implementation of photonic biosensors within point-of-care platforms is their integration with fluidic automation subsystems. For most diagnostic applications, photonic biosensors require complex fluid handling protocols; this is especially prominent in the case of competitive immunoassays, commonly used for detection of low-concentration, low-molecular weight biomarkers. For this reason, complex automated microfluidic systems are needed to realise the full point-of-care potential of photonic biosensors. To fulfil this requirement, we propose an on-chip valve-based microfluidic automation module, capable of automating such complex fluid handling. This module is realised through application of a PDMS injection moulding fabrication technique, recently described in our previous work, which enables practical fabrication of normally closed pneumatically actuated elastomeric valves. In this work, these valves are configured to achieve multiplexed reagent addressing for an on-chip diaphragm pump, providing the sample and reagent processing capabilities required for automation of cyclic competitive immunoassays. Application of this technique simplifies fabrication and introduces the potential for mass production, bringing point-of-care integration of complex automated microfluidics into the realm of practicality. This module is integrated with a highly sensitive, label-free bimodal waveguide photonic biosensor, and is demonstrated in the context of a proof-of-concept biosensing assay, detecting the low-molecular weight antibiotic tetracycline.

The Design Process of Physical Security as Applied to a U.S. Border Port of Entry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wagner, G.G.

1999-02-22

This paper details the application of a standard physical security system design process to a US Border Port of Entry (PoE) for vehicle entry/exit. The physical security design methodology is described as well as the physical security similarities to facilities currently at a US Border PoE for vehicles. The physical security design process description includes the various elements that make up the methodologies well as the considerations that must be taken into account when dealing with system integration of those elements. The distinctions between preventing unlawful entry/exit of illegal contraband and personnel are described. The potential to enhance the functionsmore » of drug/contraband detection in the Pre-Primary Inspection area through the application of emerging technologies are also addressed.« less

Radiation dose equivalent to stowaways in vehicles.

PubMed

Khan, Siraj M; Nicholas, Paul E; Terpilak, Michael S

2004-05-01

The U.S. Bureau of Customs and Border Protection has deployed a large number of non-intrusive inspection (NII) systems at land border crossings and seaports throughout the United States to inspect cars, trucks, and sea containers. These NII systems use x rays and gamma rays for the detection of contraband. Unfortunately, undocumented aliens infrequently stow away in these same conveyances to illegally enter the United States. It is extremely important that the radiation dose equivalent imparted to these stowaways be within acceptable limits. This paper discusses the issues involved and describes a protocol the U.S. Bureau of Customs and Border Protection has used in a study to measure and document these levels. The results of this study show that the radiation dose equivalent to the stowaways from the deployed NII systems is negligibly small and does not pose a health hazard.

Is there a tripeptidyl peptidase in the renal brush-border membrane?

PubMed Central

Kenny, A J; Ingram, J

1988-01-01

A recent claim that the renal brush border contains a tripeptidyl peptidase [Andersen & McDonald (1987) Am. J. Physiol. 253, F649-F655] was examined. In a fluorescent assay, the hydrolysis of Gly-Pro-Met-2-naphthylamide (-NH-Nap) and Gly-Pro-Leu-NH-Nap by pig kidney microvilli was strongly inhibited by amastatin or di-isopropyl phosphorofluoridate (inhibitors of aminopeptidases and dipeptidyl peptidase IV). The products formed were shown to be Gly-Pro and Met-NH-Nap (or Leu-NH-Nap) and free 2-naphthylamine. Specific antibodies to pig and rat aminopeptidase N abolished the apparent tripeptidyl peptidase activity. We conclude that these substrates are hydrolysed by the sequential attack of dipeptidyl peptidase IV and aminopeptidase N and that pig and rat brush borders lack a detectable tripeptidyl peptidase. Images Fig. 1. PMID:3058122

Automated acoustic analysis in detection of spontaneous swallows in Parkinson's disease.

PubMed

Golabbakhsh, Marzieh; Rajaei, Ali; Derakhshan, Mahmoud; Sadri, Saeed; Taheri, Masoud; Adibi, Peyman

2014-10-01

Acoustic monitoring of swallow frequency has become important as the frequency of spontaneous swallowing can be an index for dysphagia and related complications. In addition, it can be employed as an objective quantification of ingestive behavior. Commonly, swallowing complications are manually detected using videofluoroscopy recordings, which require expensive equipment and exposure to radiation. In this study, a noninvasive automated technique is proposed that uses breath and swallowing recordings obtained via a microphone located over the laryngopharynx. Nonlinear diffusion filters were used in which a scale-space decomposition of recorded sound at different levels extract swallows from breath sounds and artifacts. This technique was compared to manual detection of swallows using acoustic signals on a sample of 34 subjects with Parkinson's disease. A speech language pathologist identified five subjects who showed aspiration during the videofluoroscopic swallowing study. The proposed automated method identified swallows with a sensitivity of 86.67 %, a specificity of 77.50 %, and an accuracy of 82.35 %. These results indicate the validity of automated acoustic recognition of swallowing as a fast and efficient approach to objectively estimate spontaneous swallow frequency.

Automated vehicle for railway track fault detection

NASA Astrophysics Data System (ADS)

Bhushan, M.; Sujay, S.; Tushar, B.; Chitra, P.

2017-11-01

For the safety reasons, railroad tracks need to be inspected on a regular basis for detecting physical defects or design non compliances. Such track defects and non compliances, if not detected in a certain interval of time, may eventually lead to severe consequences such as train derailments. Inspection must happen twice weekly by a human inspector to maintain safety standards as there are hundreds and thousands of miles of railroad track. But in such type of manual inspection, there are many drawbacks that may result in the poor inspection of the track, due to which accidents may cause in future. So to avoid such errors and severe accidents, this automated system is designed.Such a concept would surely introduce automation in the field of inspection process of railway track and can help to avoid mishaps and severe accidents due to faults in the track.

Surveillance of borders, coastlines, and harbours (SOBCAH): a European commission preparatory action on security research

NASA Astrophysics Data System (ADS)

Clarke, David J.; Davis, Eric; Varco, Alan G.

2008-10-01

Surveillance Of Borders Coastlines And Harbours (SOBCAH ) is becoming increasingly challenging in Europe due to the expansion of new European borders coupled with the increased risks from the potential quantity and variety of terrorist activities. SOBCAH was an 18-month programme undertaken as a European Commission funded Preparatory Action in the field of Security Research (PASR) initiative to identify and demonstrate improvements in security; initially focusing on techniques to maximise the surveillance and detection effectiveness of existing sensor systems and technologies. This paper discusses the rationale in identifying the requirements, establishing a system architecture and the findings of building a security system demonstrator that underwent trials in the Port of Genoa, Italy in July 2007. It will provide an overview of the main drivers for a European-wide concept to standardise the development of enhanced border security systems. The paper will focus on techniques employed in the demonstrator to maximise the intelligence gathered from many disparate sensor sources without burdening the work load of the operators; providing enhanced situational awareness of the threat environment.

Automated model-based quantitative analysis of phantoms with spherical inserts in FDG PET scans.

PubMed

Ulrich, Ethan J; Sunderland, John J; Smith, Brian J; Mohiuddin, Imran; Parkhurst, Jessica; Plichta, Kristin A; Buatti, John M; Beichel, Reinhard R

2018-01-01

Quality control plays an increasingly important role in quantitative PET imaging and is typically performed using phantoms. The purpose of this work was to develop and validate a fully automated analysis method for two common PET/CT quality assurance phantoms: the NEMA NU-2 IQ and SNMMI/CTN oncology phantom. The algorithm was designed to only utilize the PET scan to enable the analysis of phantoms with thin-walled inserts. We introduce a model-based method for automated analysis of phantoms with spherical inserts. Models are first constructed for each type of phantom to be analyzed. A robust insert detection algorithm uses the model to locate all inserts inside the phantom. First, candidates for inserts are detected using a scale-space detection approach. Second, candidates are given an initial label using a score-based optimization algorithm. Third, a robust model fitting step aligns the phantom model to the initial labeling and fixes incorrect labels. Finally, the detected insert locations are refined and measurements are taken for each insert and several background regions. In addition, an approach for automated selection of NEMA and CTN phantom models is presented. The method was evaluated on a diverse set of 15 NEMA and 20 CTN phantom PET/CT scans. NEMA phantoms were filled with radioactive tracer solution at 9.7:1 activity ratio over background, and CTN phantoms were filled with 4:1 and 2:1 activity ratio over background. For quantitative evaluation, an independent reference standard was generated by two experts using PET/CT scans of the phantoms. In addition, the automated approach was compared against manual analysis, which represents the current clinical standard approach, of the PET phantom scans by four experts. The automated analysis method successfully detected and measured all inserts in all test phantom scans. It is a deterministic algorithm (zero variability), and the insert detection RMS error (i.e., bias) was 0.97, 1.12, and 1.48 mm for phantom activity ratios 9.7:1, 4:1, and 2:1, respectively. For all phantoms and at all contrast ratios, the average RMS error was found to be significantly lower for the proposed automated method compared to the manual analysis of the phantom scans. The uptake measurements produced by the automated method showed high correlation with the independent reference standard (R 2 ≥ 0.9987). In addition, the average computing time for the automated method was 30.6 s and was found to be significantly lower (P ≪ 0.001) compared to manual analysis (mean: 247.8 s). The proposed automated approach was found to have less error when measured against the independent reference than the manual approach. It can be easily adapted to other phantoms with spherical inserts. In addition, it eliminates inter- and intraoperator variability in PET phantom analysis and is significantly more time efficient, and therefore, represents a promising approach to facilitate and simplify PET standardization and harmonization efforts. © 2017 American Association of Physicists in Medicine.

Comparative evaluation of physicians' pulmonary nodule detection with reduced slice thickness at CT screening

NASA Astrophysics Data System (ADS)

Sinsuat, Marodina; Shimamura, Ichiro; Saita, Shinsuke; Kubo, Mitsuru; Kawata, Yoshiki; Niki, Noboru; Ohmatsu, Hironobu; Kakinuma, Ryutaro; Eguchi, Kenji; Kaneko, Masahiro; Tominaga, Keigo; Moriyama, Noriyuki

2008-03-01

With thin and thick section Multi-slice CT images at lung cancer screening, we have statistically and quantitatively shown and evaluated the diagnostic capabilities of these slice thicknesses on physicians' pulmonary nodule diagnosis. To comparatively evaluate the 2 mm and 10 mm slice thicknesses, MSCT images of 360 people were read by six physicians. The reading criteria consisted of nodule for further examination (NFE), nodule for no further examination (NNFE) and no abnormality (NA) case. For reading results evaluation; firstly, cross-tabulation was carried out to roughly analyze the diagnoses based on whole lung field and each lung lobes. Secondly, from semi-automated extraction result of the nodule, detailed quantitative analysis was carried out to determine the diagnostic capabilities of two slice thicknesses. Finally, using the reading results of 2 mm thick image as the gold standard, the diagnostic capabilities were analyzed through the features and locations of pulmonary nodules. The study revealed that both slice thicknesses can depict lung cancer. Thin section may not be effective to diagnose nodules of <=3 mm in size and nodules of <= 5mm in size for thick section. Though thick section is less tiring for reading physicians, it is not good at depicting nodules located at the border of lung upper lobe and which have a pixel size distance of <=5 from the chest wall. The information presented may serve as a useful reference to determine in which particular pulmonary nodule condition the two slice thicknesses can be effectively used for early detection of lung cancer.

Performance of Copan WASP for Routine Urine Microbiology

PubMed Central

Quiblier, Chantal; Jetter, Marion; Rominski, Mark; Mouttet, Forouhar; Böttger, Erik C.; Keller, Peter M.

2015-01-01

This study compared a manual workup of urine clinical samples with fully automated WASPLab processing. As a first step, two different inocula (1 and 10 μl) and different streaking patterns were compared using WASP and InoqulA BT instrumentation. Significantly more single colonies were produced with the10-μl inoculum than with the 1-μl inoculum, and automated streaking yielded significantly more single colonies than manual streaking on whole plates (P < 0.001). In a second step, 379 clinical urine samples were evaluated using WASP and the manual workup. Average numbers of detected morphologies, recovered species, and CFUs per milliliter of all 379 urine samples showed excellent agreement between WASPLab and the manual workup. The percentage of urine samples clinically categorized as positive or negative did not differ between the automated and manual workflow, but within the positive samples, automated processing by WASPLab resulted in the detection of more potential pathogens. In summary, the present study demonstrates that (i) the streaking pattern, i.e., primarily the number of zigzags/length of streaking lines, is critical for optimizing the number of single colonies yielded from primary cultures of urine samples; (ii) automated streaking by the WASP instrument is superior to manual streaking regarding the number of single colonies yielded (for 32.2% of the samples); and (iii) automated streaking leads to higher numbers of detected morphologies (for 47.5% of the samples), species (for 17.4% of the samples), and pathogens (for 3.4% of the samples). The results of this study point to an improved quality of microbiological analyses and laboratory reports when using automated sample processing by WASP and WASPLab. PMID:26677255

Automated choroidal neovascularization detection algorithm for optical coherence tomography angiography.

PubMed

Liu, Li; Gao, Simon S; Bailey, Steven T; Huang, David; Li, Dengwang; Jia, Yali

2015-09-01

Optical coherence tomography angiography has recently been used to visualize choroidal neovascularization (CNV) in participants with age-related macular degeneration. Identification and quantification of CNV area is important clinically for disease assessment. An automated algorithm for CNV area detection is presented in this article. It relies on denoising and a saliency detection model to overcome issues such as projection artifacts and the heterogeneity of CNV. Qualitative and quantitative evaluations were performed on scans of 7 participants. Results from the algorithm agreed well with manual delineation of CNV area.

Application of Novel Software Algorithms to Spectral-Domain Optical Coherence Tomography for Automated Detection of Diabetic Retinopathy.

PubMed

Adhi, Mehreen; Semy, Salim K; Stein, David W; Potter, Daniel M; Kuklinski, Walter S; Sleeper, Harry A; Duker, Jay S; Waheed, Nadia K

2016-05-01

To present novel software algorithms applied to spectral-domain optical coherence tomography (SD-OCT) for automated detection of diabetic retinopathy (DR). Thirty-one diabetic patients (44 eyes) and 18 healthy, nondiabetic controls (20 eyes) who underwent volumetric SD-OCT imaging and fundus photography were retrospectively identified. A retina specialist independently graded DR stage. Trained automated software generated a retinal thickness score signifying macular edema and a cluster score signifying microaneurysms and/or hard exudates for each volumetric SD-OCT. Of 44 diabetic eyes, 38 had DR and six eyes did not have DR. Leave-one-out cross-validation using a linear discriminant at missed detection/false alarm ratio of 3.00 computed software sensitivity and specificity of 92% and 69%, respectively, for DR detection when compared to clinical assessment. Novel software algorithms applied to commercially available SD-OCT can successfully detect DR and may have potential as a viable screening tool for DR in future. [Ophthalmic Surg Lasers Imaging Retina. 2016;47:410-417.]. Copyright 2016, SLACK Incorporated.

Decision support system for the detection and grading of hard exudates from color fundus photographs

NASA Astrophysics Data System (ADS)

Jaafar, Hussain F.; Nandi, Asoke K.; Al-Nuaimy, Waleed

2011-11-01

Diabetic retinopathy is a major cause of blindness, and its earliest signs include damage to the blood vessels and the formation of lesions in the retina. Automated detection and grading of hard exudates from the color fundus image is a critical step in the automated screening system for diabetic retinopathy. We propose novel methods for the detection and grading of hard exudates and the main retinal structures. For exudate detection, a novel approach based on coarse-to-fine strategy and a new image-splitting method are proposed with overall sensitivity of 93.2% and positive predictive value of 83.7% at the pixel level. The average sensitivity of the blood vessel detection is 85%, and the success rate of fovea localization is 100%. For exudate grading, a polar fovea coordinate system is adopted in accordance with medical criteria. Because of its competitive performance and ability to deal efficiently with images of variable quality, the proposed technique offers promising and efficient performance as part of an automated screening system for diabetic retinopathy.

Acoustic-sensor-based detection of damage in composite aircraft structures

NASA Astrophysics Data System (ADS)

Foote, Peter; Martin, Tony; Read, Ian

2004-03-01

Acoustic emission detection is a well-established method of locating and monitoring crack development in metal structures. The technique has been adapted to test facilities for non-destructive testing applications. Deployment as an operational or on-line automated damage detection technology in vehicles is posing greater challenges. A clear requirement of potential end-users of such systems is a level of automation capable of delivering low-level diagnosis information. The output from the system is in the form of "go", "no-go" indications of structural integrity or immediate maintenance actions. This level of automation requires significant data reduction and processing. This paper describes recent trials of acoustic emission detection technology for the diagnosis of damage in composite aerospace structures. The technology comprises low profile detection sensors using piezo electric wafers encapsulated in polymer film ad optical sensors. Sensors are bonded to the structure"s surface and enable acoustic events from the loaded structure to be located by triangulation. Instrumentation has been enveloped to capture and parameterise the sensor data in a form suitable for low-bandwidth storage and transmission.

Electroencephalogram Signal Classification for Automated Epileptic Seizure Detection Using Genetic Algorithm

PubMed Central

Nanthini, B. Suguna; Santhi, B.

2017-01-01

Background: Epilepsy causes when the repeated seizure occurs in the brain. Electroencephalogram (EEG) test provides valuable information about the brain functions and can be useful to detect brain disorder, especially for epilepsy. In this study, application for an automated seizure detection model has been introduced successfully. Materials and Methods: The EEG signals are decomposed into sub-bands by discrete wavelet transform using db2 (daubechies) wavelet. The eight statistical features, the four gray level co-occurrence matrix and Renyi entropy estimation with four different degrees of order, are extracted from the raw EEG and its sub-bands. Genetic algorithm (GA) is used to select eight relevant features from the 16 dimension features. The model has been trained and tested using support vector machine (SVM) classifier successfully for EEG signals. The performance of the SVM classifier is evaluated for two different databases. Results: The study has been experimented through two different analyses and achieved satisfactory performance for automated seizure detection using relevant features as the input to the SVM classifier. Conclusion: Relevant features using GA give better accuracy performance for seizure detection. PMID:28781480

Phase editing as a signal pre-processing step for automated bearing fault detection

NASA Astrophysics Data System (ADS)

Barbini, L.; Ompusunggu, A. P.; Hillis, A. J.; du Bois, J. L.; Bartic, A.

2017-07-01

Scheduled maintenance and inspection of bearing elements in industrial machinery contributes significantly to the operating costs. Savings can be made through automatic vibration-based damage detection and prognostics, to permit condition-based maintenance. However automation of the detection process is difficult due to the complexity of vibration signals in realistic operating environments. The sensitivity of existing methods to the choice of parameters imposes a requirement for oversight from a skilled operator. This paper presents a novel approach to the removal of unwanted vibrational components from the signal: phase editing. The approach uses a computationally-efficient full-band demodulation and requires very little oversight. Its effectiveness is tested on experimental data sets from three different test-rigs, and comparisons are made with two state-of-the-art processing techniques: spectral kurtosis and cepstral pre- whitening. The results from the phase editing technique show a 10% improvement in damage detection rates compared to the state-of-the-art while simultaneously improving on the degree of automation. This outcome represents a significant contribution in the pursuit of fully automatic fault detection.

Understanding human management of automation errors

PubMed Central

McBride, Sara E.; Rogers, Wendy A.; Fisk, Arthur D.

2013-01-01

Automation has the potential to aid humans with a diverse set of tasks and support overall system performance. Automated systems are not always reliable, and when automation errs, humans must engage in error management, which is the process of detecting, understanding, and correcting errors. However, this process of error management in the context of human-automation interaction is not well understood. Therefore, we conducted a systematic review of the variables that contribute to error management. We examined relevant research in human-automation interaction and human error to identify critical automation, person, task, and emergent variables. We propose a framework for management of automation errors to incorporate and build upon previous models. Further, our analysis highlights variables that may be addressed through design and training to positively influence error management. Additional efforts to understand the error management process will contribute to automation designed and implemented to support safe and effective system performance. PMID:25383042

Automation Bias: Decision Making and Performance in High-Tech Cockpits

NASA Technical Reports Server (NTRS)

Mosier, Kathleen L.; Skitka, Linda J.; Heers, Susan; Burdick, Mark; Rosekind, Mark R. (Technical Monitor)

1997-01-01

Automated aids and decision support tools are rapidly becoming indispensible tools in high-technology cockpits, and are assuming increasing control of "cognitive" flight tasks, such as calculating fuel-efficient routes, navigating, or detecting and diagnosing system malfunctions and abnormalities. This study was designed to investigate "automation bias," a recently documented factor in the use of automated aids and decision support systems. The term refers to omission and commission errors resulting from the use of automated cues as a heuristic replacement for vigilant information seeking and processing. Glass-cockpit pilots flew flight scenarios involving automation "events," or opportunities for automation-related omission and commission errors. Pilots who perceived themselves as "accountable" for their performance and strategies of interaction with the automation were more likely to double-check automated functioning against other cues, and less likely to commit errors. Pilots were also likely to erroneously "remember" the presence of expected cues when describing their decision-making processes.

Understanding human management of automation errors.

PubMed

McBride, Sara E; Rogers, Wendy A; Fisk, Arthur D

2014-01-01

Automation has the potential to aid humans with a diverse set of tasks and support overall system performance. Automated systems are not always reliable, and when automation errs, humans must engage in error management, which is the process of detecting, understanding, and correcting errors. However, this process of error management in the context of human-automation interaction is not well understood. Therefore, we conducted a systematic review of the variables that contribute to error management. We examined relevant research in human-automation interaction and human error to identify critical automation, person, task, and emergent variables. We propose a framework for management of automation errors to incorporate and build upon previous models. Further, our analysis highlights variables that may be addressed through design and training to positively influence error management. Additional efforts to understand the error management process will contribute to automation designed and implemented to support safe and effective system performance.

Applied Actant Network Theory: Toward the Automated Detection of Technoscientific Emergence from Full Text Publications and Patents (Open Access)

DTIC Science & Technology

2012-11-02

Applied Actant-Network Theory: Toward the Automated Detection of Technoscientific Emergence from Full-Text Publications and Patents David C...Brock**, Olga Babko-Malaya*, James Pustejovsky***, Patrick Thomas****, *BAE Systems Advanced Information Technologies, ** David C. Brock Consulting... Wojick , D. 2008. Population modeling of the emergence and development of scientific fields. Scientometrics, 75(3):495–518. Cook, T. D. and

The astro-geodetic use of CCD for gravity field refinement

NASA Astrophysics Data System (ADS)

Gerstbach, G.

1996-07-01

The paper starts with a review of geoid projects, where vertical deflections are more effective than gravimetry. In alpine regions the economy of astrogeoids is at least 10 times higher, but many countries do not make use of this fact - presumably because the measurements are not fully automated up to now. Based upon the experiences of astrometry of high satellites and own tests the author analyses the use of CCD for astro-geodetic measurements. Automation and speeding up will be possible in a few years, the latter depending on the observation scheme. Sensor characteristics, cooling and reading out of the devices should be harmonized. Using line sensors in small prism astrolabes, the CCD accuracy will reach the visual one (±0.2″) within 5-10 years. Astrogeoids can be combined ideally with geological data, because vertical variation of rock densities does not cause systematic effects (contrary to gravimetry). So a geoid of ±5 cm accuracy (achieved in Austria and other alpine countries by 5-10 points per 1000 km 2) can be improved to ±2 cm without additional observations and border effects.

Long-Term Pavement Performance Automated Faulting Measurement

DOT National Transportation Integrated Search

2015-02-01

This study focused on identifying transverse joint locations on jointed plain concrete pavements using an automated joint detection algorithm and computing faulting at these locations using Long-Term Pavement Performance (LTPP) Program profile data c...

Advanced Technologies and Methodology for Automated Ultrasonic Testing Systems Quantification

DOT National Transportation Integrated Search

2011-04-29

For automated ultrasonic testing (AUT) detection and sizing accuracy, this program developed a methodology for quantification of AUT systems, advancing and quantifying AUT systems imagecapture capabilities, quantifying the performance of multiple AUT...

1366 Project Automate: Enabling Automation for <$0.10/W High-Efficiency Kerfless Wafers Manufactured in the US

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lorenz, Adam

For photovoltaic (PV) manufacturing to thrive in the U.S., there must be an innovative core to the technology. Project Automate builds on 1366’s proprietary Direct Wafer® kerfless wafer technology and aims to unlock the cost and efficiency advantages of thin kerfless wafers. Direct Wafer is an innovative, U.S.-friendly (efficient, low-labor content) manufacturing process that addresses the main cost barrier limiting silicon PV cost-reductions – the 35-year-old grand challenge of manufacturing quality wafers (40% of the cost of modules) without the cost and waste of sawing. This simple, scalable process will allow 1366 to manufacture “drop-in” replacement wafers for the $10more » billion silicon PV wafer market at 50% of the cost, 60% of the capital, and 30% of the electricity of conventional casting and sawing manufacturing processes. This SolarMat project developed the Direct Wafer processes’ unique capability to tailor the shape of wafers to simultaneously make thinner AND stronger wafers (with lower silicon usage) that enable high-efficiency cell architectures. By producing wafers with a unique target geometry including a thick border (which determines handling characteristics) and thin interior regions (which control light capture and electron transport and therefore determine efficiency), 1366 can simultaneously improve quality and lower cost (using less silicon).« less

First detection of foot-and-mouth disease virus O/Ind-2001d in Vietnam

USDA-ARS?s Scientific Manuscript database

In recent years, foot-and-mouth disease virus (FMDV) serotype O, lineage Ind2001d has spread to the Middle East, North Africa, and Southeast Asia. In the current report, we describe the first detection of this lineage in Vietnam in May, 2015 in Dak Nong province which borders Cambodia. Three subsequ...

Information Systems to Support Surveillance for Malaria Elimination

PubMed Central

Ohrt, Colin; Roberts, Kathryn W.; Sturrock, Hugh J. W.; Wegbreit, Jennifer; Lee, Bruce Y.; Gosling, Roly D.

2015-01-01

Robust and responsive surveillance systems are critical for malaria elimination. The ideal information system that supports malaria elimination includes: rapid and complete case reporting, incorporation of related data, such as census or health survey information, central data storage and management, automated and expert data analysis, and customized outputs and feedback that lead to timely and targeted responses. Spatial information enhances such a system, ensuring cases are tracked and mapped over time. Data sharing and coordination across borders are vital and new technologies can improve data speed, accuracy, and quality. Parts of this ideal information system exist and are in use, but have yet to be linked together coherently. Malaria elimination programs should support the implementation and refinement of information systems to support surveillance and response and ensure political and financial commitment to maintain the systems and the human resources needed to run them. National malaria programs should strive to improve the access and utility of these information systems and establish cross-border data sharing mechanisms through the use of standard indicators for malaria surveillance. Ultimately, investment in the information technologies that support a timely and targeted surveillance and response system is essential for malaria elimination. PMID:26013378

Information systems to support surveillance for malaria elimination.

PubMed

Ohrt, Colin; Roberts, Kathryn W; Sturrock, Hugh J W; Wegbreit, Jennifer; Lee, Bruce Y; Gosling, Roly D

2015-07-01

Robust and responsive surveillance systems are critical for malaria elimination. The ideal information system that supports malaria elimination includes: rapid and complete case reporting, incorporation of related data, such as census or health survey information, central data storage and management, automated and expert data analysis, and customized outputs and feedback that lead to timely and targeted responses. Spatial information enhances such a system, ensuring cases are tracked and mapped over time. Data sharing and coordination across borders are vital and new technologies can improve data speed, accuracy, and quality. Parts of this ideal information system exist and are in use, but have yet to be linked together coherently. Malaria elimination programs should support the implementation and refinement of information systems to support surveillance and response and ensure political and financial commitment to maintain the systems and the human resources needed to run them. National malaria programs should strive to improve the access and utility of these information systems and establish cross-border data sharing mechanisms through the use of standard indicators for malaria surveillance. Ultimately, investment in the information technologies that support a timely and targeted surveillance and response system is essential for malaria elimination. © The American Society of Tropical Medicine and Hygiene.

Automated Coding Software: Development and Use to Enhance Anti-Fraud Activities*

PubMed Central

Garvin, Jennifer H.; Watzlaf, Valerie; Moeini, Sohrab

2006-01-01

This descriptive research project identified characteristics of automated coding systems that have the potential to detect improper coding and to minimize improper or fraudulent coding practices in the setting of automated coding used with the electronic health record (EHR). Recommendations were also developed for software developers and users of coding products to maximize anti-fraud practices. PMID:17238546

Automated detection of extradural and subdural hematoma for contrast-enhanced CT images in emergency medical care

NASA Astrophysics Data System (ADS)

Hara, Takeshi; Matoba, Naoto; Zhou, Xiangrong; Yokoi, Shinya; Aizawa, Hiroaki; Fujita, Hiroshi; Sakashita, Keiji; Matsuoka, Tetsuya

2007-03-01

We have been developing the CAD scheme for head and abdominal injuries for emergency medical care. In this work, we have developed an automated method to detect typical head injuries, rupture or strokes of brain. Extradural and subdural hematoma region were detected by comparing technique after the brain areas were registered using warping. We employ 5 normal and 15 stroke cases to estimate the performance after creating the brain model with 50 normal cases. Some of the hematoma regions were detected correctly in all of the stroke cases with no false positive findings on normal cases.

Filament Chirality over an Entire Cycle Determined with an Automated Detection Module -- a Neat Surprise!

NASA Astrophysics Data System (ADS)

Martens, Petrus C.; Yeates, A. R.; Mackay, D.; Pillai, K. G.

2013-07-01

Using metadata produced by automated solar feature detection modules developed for SDO (Martens et al. 2012) we have discovered some trends in filament chirality and filament-sigmoid relations that are new and in part contradict the current consensus. Automated detection of solar features has the advantage over manual detection of having the detection criteria applied consistently, and in being able to deal with enormous amounts of data, like the 1 Terabyte per day that SDO produces. Here we use the filament detection module developed by Bernasconi, which has metadata from 2000 on, and the sigmoid sniffer, which has been producing metadata from AIA 94 A images since October 2011. The most interesting result we find is that the hemispheric chirality preference for filaments (dextral in the north, and v.v.), studied in detail for a three year period by Pevtsov et al. (2003) seems to disappear during parts of the decline of cycle 23 and during the extended solar minimum that followed. Moreover the hemispheric chirality rule seems to be much less pronounced during the onset of cycle 24. For sigmoids we find the expected correlation between chirality and handedness (S or Z) shape but not as strong as expected.

Mapping the Recent US Hurricanes Triggered Flood Events in Near Real Time

NASA Astrophysics Data System (ADS)

Shen, X.; Lazin, R.; Anagnostou, E. N.; Wanik, D. W.; Brakenridge, G. R.

2017-12-01

Synthetic Aperture Radar (SAR) observations is the only reliable remote sensing data source to map flood inundation during severe weather events. Unfortunately, since state-of-art data processing algorithms cannot meet the automation and quality standard of a near-real-time (NRT) system, quality controlled inundation mapping by SAR currently depends heavily on manual processing, which limits our capability to quickly issue flood inundation maps at global scale. Specifically, most SAR-based inundation mapping algorithms are not fully automated, while those that are automated exhibit severe over- and/or under-detection errors that limit their potential. These detection errors are primarily caused by the strong overlap among the SAR backscattering probability density functions (PDF) of different land cover types. In this study, we tested a newly developed NRT SAR-based inundation mapping system, named Radar Produced Inundation Diary (RAPID), using Sentinel-1 dual polarized SAR data over recent flood events caused by Hurricanes Harvey, Irma, and Maria (2017). The system consists of 1) self-optimized multi-threshold classification, 2) over-detection removal using land-cover information and change detection, 3) under-detection compensation, and 4) machine-learning based correction. Algorithm details are introduced in another poster, H53J-1603. Good agreements were obtained by comparing the result from RAPID with visual interpretation of SAR images and manual processing from Dartmouth Flood Observatory (DFO) (See Figure 1). Specifically, the over- and under-detections that is typically noted in automated methods is significantly reduced to negligible levels. This performance indicates that RAPID can address the automation and accuracy issues of current state-of-art algorithms and has the potential to apply operationally on a number of satellite SAR missions, such as SWOT, ALOS, Sentinel etc. RAPID data can support many applications such as rapid assessment of damage losses and disaster alleviation/rescue at global scale.

Flight deck disturbance management: a simulator study of diagnosis and recovery from breakdowns in pilot-automation coordination.

PubMed

Nikolic, Mark I; Sarter, Nadine B

2007-08-01

To examine operator strategies for diagnosing and recovering from errors and disturbances as well as the impact of automation design and time pressure on these processes. Considerable efforts have been directed at error prevention through training and design. However, because errors cannot be eliminated completely, their detection, diagnosis, and recovery must also be supported. Research has focused almost exclusively on error detection. Little is known about error diagnosis and recovery, especially in the context of event-driven tasks and domains. With a confederate pilot, 12 airline pilots flew a 1-hr simulator scenario that involved three challenging automation-related tasks and events that were likely to produce erroneous actions or assessments. Behavioral data were compared with a canonical path to examine pilots' error and disturbance management strategies. Debriefings were conducted to probe pilots' system knowledge. Pilots seldom followed the canonical path to cope with the scenario events. Detection of a disturbance was often delayed. Diagnostic episodes were rare because of pilots' knowledge gaps and time criticality. In many cases, generic inefficient recovery strategies were observed, and pilots relied on high levels of automation to manage the consequences of an error. Our findings describe and explain the nature and shortcomings of pilots' error management activities. They highlight the need for improved automation training and design to achieve more timely detection, accurate explanation, and effective recovery from errors and disturbances. Our findings can inform the design of tools and techniques that support disturbance management in various complex, event-driven environments.

Automated Analysis of Fluorescence Microscopy Images to Identify Protein-Protein Interactions

DOE PAGES

Venkatraman, S.; Doktycz, M. J.; Qi, H.; ...

2006-01-01

The identification of protein interactions is important for elucidating biological networks. One obstacle in comprehensive interaction studies is the analyses of large datasets, particularly those containing images. Development of an automated system to analyze an image-based protein interaction dataset is needed. Such an analysis system is described here, to automatically extract features from fluorescence microscopy images obtained from a bacterial protein interaction assay. These features are used to relay quantitative values that aid in the automated scoring of positive interactions. Experimental observations indicate that identifying at least 50% positive cells in an image is sufficient to detect a protein interaction.more » Based on this criterion, the automated system presents 100% accuracy in detecting positive interactions for a dataset of 16 images. Algorithms were implemented using MATLAB and the software developed is available on request from the authors.« less

Automated diabetic retinopathy detection in smartphone-based fundus photography using artificial intelligence.

PubMed

Rajalakshmi, Ramachandran; Subashini, Radhakrishnan; Anjana, Ranjit Mohan; Mohan, Viswanathan

2018-06-01

To assess the role of artificial intelligence (AI)-based automated software for detection of diabetic retinopathy (DR) and sight-threatening DR (STDR) by fundus photography taken using a smartphone-based device and validate it against ophthalmologist's grading. Three hundred and one patients with type 2 diabetes underwent retinal photography with Remidio 'Fundus on phone' (FOP), a smartphone-based device, at a tertiary care diabetes centre in India. Grading of DR was performed by the ophthalmologists using International Clinical DR (ICDR) classification scale. STDR was defined by the presence of severe non-proliferative DR, proliferative DR or diabetic macular oedema (DME). The retinal photographs were graded using a validated AI DR screening software (EyeArt TM ) designed to identify DR, referable DR (moderate non-proliferative DR or worse and/or DME) or STDR. The sensitivity and specificity of automated grading were assessed and validated against the ophthalmologists' grading. Retinal images of 296 patients were graded. DR was detected by the ophthalmologists in 191 (64.5%) and by the AI software in 203 (68.6%) patients while STDR was detected in 112 (37.8%) and 146 (49.3%) patients, respectively. The AI software showed 95.8% (95% CI 92.9-98.7) sensitivity and 80.2% (95% CI 72.6-87.8) specificity for detecting any DR and 99.1% (95% CI 95.1-99.9) sensitivity and 80.4% (95% CI 73.9-85.9) specificity in detecting STDR with a kappa agreement of k = 0.78 (p < 0.001) and k = 0.75 (p < 0.001), respectively. Automated AI analysis of FOP smartphone retinal imaging has very high sensitivity for detecting DR and STDR and thus can be an initial tool for mass retinal screening in people with diabetes.

Vertebra identification using template matching modelmp and K-means clustering.

PubMed

Larhmam, Mohamed Amine; Benjelloun, Mohammed; Mahmoudi, Saïd

2014-03-01

Accurate vertebra detection and segmentation are essential steps for automating the diagnosis of spinal disorders. This study is dedicated to vertebra alignment measurement, the first step in a computer-aided diagnosis tool for cervical spine trauma. Automated vertebral segment alignment determination is a challenging task due to low contrast imaging and noise. A software tool for segmenting vertebrae and detecting subluxations has clinical significance. A robust method was developed and tested for cervical vertebra identification and segmentation that extracts parameters used for vertebra alignment measurement. Our contribution involves a novel combination of a template matching method and an unsupervised clustering algorithm. In this method, we build a geometric vertebra mean model. To achieve vertebra detection, manual selection of the region of interest is performed initially on the input image. Subsequent preprocessing is done to enhance image contrast and detect edges. Candidate vertebra localization is then carried out by using a modified generalized Hough transform (GHT). Next, an adapted cost function is used to compute local voted centers and filter boundary data. Thereafter, a K-means clustering algorithm is applied to obtain clusters distribution corresponding to the targeted vertebrae. These clusters are combined with the vote parameters to detect vertebra centers. Rigid segmentation is then carried out by using GHT parameters. Finally, cervical spine curves are extracted to measure vertebra alignment. The proposed approach was successfully applied to a set of 66 high-resolution X-ray images. Robust detection was achieved in 97.5 % of the 330 tested cervical vertebrae. An automated vertebral identification method was developed and demonstrated to be robust to noise and occlusion. This work presents a first step toward an automated computer-aided diagnosis system for cervical spine trauma detection.

An Automated Quiet Sleep Detection Approach in Preterm Infants as a Gateway to Assess Brain Maturation.

PubMed

Dereymaeker, Anneleen; Pillay, Kirubin; Vervisch, Jan; Van Huffel, Sabine; Naulaers, Gunnar; Jansen, Katrien; De Vos, Maarten

2017-09-01

Sleep state development in preterm neonates can provide crucial information regarding functional brain maturation and give insight into neurological well being. However, visual labeling of sleep stages from EEG requires expertise and is very time consuming, prompting the need for an automated procedure. We present a robust method for automated detection of preterm sleep from EEG, over a wide postmenstrual age ([Formula: see text] age) range, focusing first on Quiet Sleep (QS) as an initial marker for sleep assessment. Our algorithm, CLuster-based Adaptive Sleep Staging (CLASS), detects QS if it remains relatively more discontinuous than non-QS over PMA. CLASS was optimized on a training set of 34 recordings aged 27-42 weeks PMA, and performance then assessed on a distinct test set of 55 recordings of the same age range. Results were compared to visual QS labeling from two independent raters (with inter-rater agreement [Formula: see text]), using Sensitivity, Specificity, Detection Factor ([Formula: see text] of visual QS periods correctly detected by CLASS) and Misclassification Factor ([Formula: see text] of CLASS-detected QS periods that are misclassified). CLASS performance proved optimal across recordings at 31-38 weeks (median [Formula: see text], median MF 0-0.25, median Sensitivity 0.93-1.0, and median Specificity 0.80-0.91 across this age range), with minimal misclassifications at 35-36 weeks (median [Formula: see text]). To illustrate the potential of CLASS in facilitating clinical research, normal maturational trends over PMA were derived from CLASS-estimated QS periods, visual QS estimates, and nonstate specific periods (containing QS and non-QS) in the EEG recording. CLASS QS trends agreed with those from visual QS, with both showing stronger correlations than nonstate specific trends. This highlights the benefit of automated QS detection for exploring brain maturation.

Cross border ITS systems with traffic management centers : project summary.

DOT National Transportation Integrated Search

2016-07-31

Traffic management centers (TMCs) in Texas play a : vital role in managing traffic operations in many : major metropolitan areas. TMCs have deployed : extensive detection, monitoring, and communication : infrastructure to allow Texas Department of : ...

A standardized staining protocol for L1CAM on formalin-fixed, paraffin-embedded tissues using automated platforms.

PubMed

Fogel, Mina; Harari, Ayelet; Müller-Holzner, Elisabeth; Zeimet, Alain G; Moldenhauer, Gerhard; Altevogt, Peter

2014-06-25

The L1 cell adhesion molecule (L1CAM) is overexpressed in many human cancers and can serve as a biomarker for prognosis in most of these cancers (including type I endometrial carcinomas). Here we provide an optimized immunohistochemical staining procedure for a widely used automated platform (VENTANA™), which has recourse to commercially available primary antibody and detection reagents. In parallel, we optimized the staining on a semi-automated BioGenix (i6000) 
immunostainer. These protocols yield good stainings and should represent the basis for a reliable and standardized immunohistochemical detection of L1CAM in a variety of malignancies in different laboratories.

Integrated Multi-process Microfluidic Systems for Automating Analysis

PubMed Central

Yang, Weichun; Woolley, Adam T.

2010-01-01

Microfluidic technologies have been applied extensively in rapid sample analysis. Some current challenges for standard microfluidic systems are relatively high detection limits, and reduced resolving power and peak capacity compared to conventional approaches. The integration of multiple functions and components onto a single platform can overcome these separation and detection limitations of microfluidics. Multiplexed systems can greatly increase peak capacity in multidimensional separations and can increase sample throughput by analyzing many samples simultaneously. On-chip sample preparation, including labeling, preconcentration, cleanup and amplification, can all serve to speed up and automate processes in integrated microfluidic systems. This paper summarizes advances in integrated multi-process microfluidic systems for automated analysis, their benefits and areas for needed improvement. PMID:20514343

Airborne Particulate Threat Assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patrick Treado; Oksana Klueva; Jeffrey Beckstead

Aerosol threat detection requires the ability to discern between threat agents and ambient background particulate matter (PM) encountered in the environment. To date, Raman imaging technology has been demonstrated as an effective strategy for the assessment of threat agents in the presence of specific, complex backgrounds. Expanding our understanding of the composition of ambient particulate matter background will improve the overall performance of Raman Chemical Imaging (RCI) detection strategies for the autonomous detection of airborne chemical and biological hazards. Improving RCI detection performance is strategic due to its potential to become a widely exploited detection approach by several U.S. governmentmore » agencies. To improve the understanding of the ambient PM background with subsequent improvement in Raman threat detection capability, ChemImage undertook the Airborne Particulate Threat Assessment (APTA) Project in 2005-2008 through a collaborative effort with the National Energy Technology Laboratory (NETL), under cooperative agreement number DE-FC26-05NT42594. During Phase 1 of the program, a novel PM classification based on molecular composition was developed based on a comprehensive review of the scientific literature. In addition, testing protocols were developed for ambient PM characterization. A signature database was developed based on a variety of microanalytical techniques, including scanning electron microscopy, FT-IR microspectroscopy, optical microscopy, fluorescence and Raman chemical imaging techniques. An automated particle integrated collector and detector (APICD) prototype was developed for automated collection, deposition and detection of biothreat agents in background PM. During Phase 2 of the program, ChemImage continued to refine the understanding of ambient background composition. Additionally, ChemImage enhanced the APICD to provide improved autonomy, sensitivity and specificity. Deliverables included a Final Report detailing our findings and APICD Gen II subsystems for automated collection, deposition and detection of ambient particulate matter. Key findings from the APTA Program include: Ambient biological PM taxonomy; Demonstration of key subsystems needed for autonomous bioaerosol detection; System design; Efficient electrostatic collection; Automated bioagent recognition; Raman analysis performance validating Td<9 sec; Efficient collection surface regeneration; and Development of a quantitative bioaerosol defection model. The objective of the APTA program was to advance the state of our knowledge of ambient background PM composition. Operation of an automated aerosol detection system was enhanced by a more accurate assessment of background variability, especially for sensitive and specific sensing strategies like Raman detection that are background-limited in performance. Based on this improved knowledge of background, the overall threat detection performance of Raman sensors was improved.« less

A graphical automated detection system to locate hardwood log surface defects using high-resolution three-dimensional laser scan data

Treesearch

Liya Thomas; R. Edward Thomas

2011-01-01

We have developed an automated defect detection system and a state-of-the-art Graphic User Interface (GUI) for hardwood logs. The algorithm identifies defects at least 0.5 inch high and at least 3 inches in diameter on barked hardwood log and stem surfaces. To summarize defect features and to build a knowledge base, hundreds of defects were measured, photographed, and...

An Automated Energy Detection Algorithm Based on Morphological Filter Processing with a Modified Watershed Transform

DTIC Science & Technology

2018-01-01

collected data. These statistical techniques are under the area of descriptive statistics, which is a methodology to condense the data in quantitative ...ARL-TR-8270 ● JAN 2018 US Army Research Laboratory An Automated Energy Detection Algorithm Based on Morphological Filter...report when it is no longer needed. Do not return it to the originator. ARL-TR-8270 ● JAN 2017 US Army Research Laboratory An

Topography-Assisted Electromagnetic Platform for Blood-to-PCR in a Droplet

PubMed Central

Chiou, Chi-Han; Shin, Dong Jin; Zhang, Yi; Wang, Tza-Huei

2013-01-01

This paper presents an electromagnetically actuated platform for automated sample preparation and detection of nucleic acids. The proposed platform integrates nucleic acid extraction using silica-coated magnetic particles with real-time polymerase chain reaction (PCR) on a single cartridge. Extraction of genomic material was automated by manipulating magnetic particles in droplets using a series of planar coil electromagnets assisted by topographical features, enabling efficient fluidic processing over a variety of buffers and reagents. The functionality of the platform was demonstrated by performing nucleic acid extraction from whole blood, followed by real-time PCR detection of KRAS oncogene. Automated sample processing from whole blood to PCR-ready droplet was performed in 15 minutes. We took a modular approach of decoupling the modules of magnetic manipulation and optical detection from the device itself, enabling a low-complexity cartridge that operates in tandem with simple external instruments. PMID:23835223

CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation

PubMed Central

2013-01-01

The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm, the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening. PMID:23938087

CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation.

PubMed

Hodneland, Erlend; Kögel, Tanja; Frei, Dominik Michael; Gerdes, Hans-Hermann; Lundervold, Arvid

2013-08-09

: The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm, the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening.

Automated detection of geological landforms on Mars using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Palafox, Leon F.; Hamilton, Christopher W.; Scheidt, Stephen P.; Alvarez, Alexander M.

2017-04-01

The large volume of high-resolution images acquired by the Mars Reconnaissance Orbiter has opened a new frontier for developing automated approaches to detecting landforms on the surface of Mars. However, most landform classifiers focus on crater detection, which represents only one of many geological landforms of scientific interest. In this work, we use Convolutional Neural Networks (ConvNets) to detect both volcanic rootless cones and transverse aeolian ridges. Our system, named MarsNet, consists of five networks, each of which is trained to detect landforms of different sizes. We compare our detection algorithm with a widely used method for image recognition, Support Vector Machines (SVMs) using Histogram of Oriented Gradients (HOG) features. We show that ConvNets can detect a wide range of landforms and has better accuracy and recall in testing data than traditional classifiers based on SVMs.

Automated detection of geological landforms on Mars using Convolutional Neural Networks.

PubMed

Palafox, Leon F; Hamilton, Christopher W; Scheidt, Stephen P; Alvarez, Alexander M

2017-04-01

The large volume of high-resolution images acquired by the Mars Reconnaissance Orbiter has opened a new frontier for developing automated approaches to detecting landforms on the surface of Mars. However, most landform classifiers focus on crater detection, which represents only one of many geological landforms of scientific interest. In this work, we use Convolutional Neural Networks (ConvNets) to detect both volcanic rootless cones and transverse aeolian ridges. Our system, named MarsNet, consists of five networks, each of which is trained to detect landforms of different sizes. We compare our detection algorithm with a widely used method for image recognition, Support Vector Machines (SVMs) using Histogram of Oriented Gradients (HOG) features. We show that ConvNets can detect a wide range of landforms and has better accuracy and recall in testing data than traditional classifiers based on SVMs.

Automatic Extraction of High-Resolution Rainfall Series from Rainfall Strip Charts

NASA Astrophysics Data System (ADS)

Saa-Requejo, Antonio; Valencia, Jose Luis; Garrido, Alberto; Tarquis, Ana M.

2015-04-01

Soil erosion is a complex phenomenon involving the detachment and transport of soil particles, storage and runoff of rainwater, and infiltration. The relative magnitude and importance of these processes depends on a host of factors, including climate, soil, topography, cropping and land management practices among others. Most models for soil erosion or hydrological processes need an accurate storm characterization. However, this data are not always available and in some cases indirect models are generated to fill this gap. In Spain, the rain intensity data known for time periods less than 24 hours back to 1924 and many studies are limited by it. In many cases this data is stored in rainfall strip charts in the meteorological stations but haven't been transfer in a numerical form. To overcome this deficiency in the raw data a process of information extraction from large amounts of rainfall strip charts is implemented by means of computer software. The method has been developed that largely automates the intensive-labour extraction work based on van Piggelen et al. (2011). The method consists of the following five basic steps: 1) scanning the charts to high-resolution digital images, 2) manually and visually registering relevant meta information from charts and pre-processing, 3) applying automatic curve extraction software in a batch process to determine the coordinates of cumulative rainfall lines on the images (main step), 4) post processing the curves that were not correctly determined in step 3, and 5) aggregating the cumulative rainfall in pixel coordinates to the desired time resolution. A colour detection procedure is introduced that automatically separates the background of the charts and rolls from the grid and subsequently the rainfall curve. The rainfall curve is detected by minimization of a cost function. Some utilities have been added to improve the previous work and automates some auxiliary processes: readjust the bands properly, merge bands when those have been scanned in two parts, detect and cut the borders of bands not used (demanded by the software). Also some variations in which colour system is tried basing in HUE or RGB colour have been included. Thanks to apply this digitization rainfall strip charts 209 station-years of three locations in the centre of Spain have been transformed to long-term rainfall time series with 5-min resolution. References van Piggelen, H.E., T. Brandsma, H. Manders, and J. F. Lichtenauer, 2011: Automatic Curve Extraction for Digitizing Rainfall Strip Charts. J. Atmos. Oceanic Technol., 28, 891-906. Acknowledgements Financial support for this research by DURERO Project (Env.C1.3913442) is greatly appreciated.

Experimental studies on the effect of automation on pilot situational awareness in the datalink ATC environment

NASA Technical Reports Server (NTRS)

Hahn, Edward C.; Hansman, R. J., Jr.

1992-01-01

An experiment to study how automation, when used in conjunction with datalink for the delivery of ATC clearance amendments, affects the situational awareness of aircrews was conducted. The study was focused on the relationship of situational awareness to automated Flight Management System (FMS) programming of datalinked clearances and the readback of ATC clearances. Situational awareness was tested by issuing nominally unacceptable ATC clearances and measuring whether the error was detected by the subject pilots. The experiment also varied the mode of clearance delivery: Verbal, Textual, and Graphical. The error detection performance and pilot preference results indicate that the automated programming of the FMS may be superior to manual programming. It is believed that automated FMS programming may relieve some of the cognitive load, allowing pilots to concentrate on the strategic implications of a clearance amendment. Also, readback appears to have value, but the small sample size precludes a definite conclusion. Furthermore, because textual and graphical modes of delivery offer different but complementary advantages for cognitive processing, a combination of these modes of delivery may be advantageous in a datalink presentation.

An Experimental Study of the Effects of Automation on Pilot Situational Awareness in the Datalink ATC Environment

NASA Technical Reports Server (NTRS)

Hahn, Edward C.; Hansman, R. John, Jr.

1992-01-01

An experiment to study how automation, when used in conjunction with datalink for the delivery of air traffic control (ATC) clearance amendments, affects the situational awareness of aircrews was conducted. The study was focused on the relationship of situational awareness to automated Flight Management System (FMS) programming and the readback of ATC clearances. Situational awareness was tested by issuing nominally unacceptable ATC clearances and measuring whether the error was detected by the subject pilots. The experiment also varied the mode of clearance delivery: Verbal, Textual, and Graphical. The error detection performance and pilot preference results indicate that the automated programming of the FMS may be superior to manual programming. It is believed that automated FMS programming may relieve some of the cognitive load, allowing pilots to concentrate on the strategic implications of a clearance amendment. Also, readback appears to have value, but the small sample size precludes a definite conclusion. Furthermore, because textual and graphical modes of delivery offer different but complementary advantages for cognitive processing, a combination of these modes of delivery may be advantageous in a datalink presentation.

Automated analysis of oxidative metabolites

NASA Technical Reports Server (NTRS)

Furner, R. L. (Inventor)

1974-01-01

An automated system for the study of drug metabolism is described. The system monitors the oxidative metabolites of aromatic amines and of compounds which produce formaldehyde on oxidative dealkylation. It includes color developing compositions suitable for detecting hyroxylated aromatic amines and formaldehyde.

Genetic diversity of the Plasmodium falciparum apical membrane antigen I gene in parasite population from the China-Myanmar border area.

PubMed

Zhu, Xiaotong; Zhao, Zhenjun; Feng, Yonghui; Li, Peipei; Liu, Fei; Liu, Jun; Yang, Zhaoqing; Yan, Guiyun; Fan, Qi; Cao, Yaming; Cui, Liwang

2016-04-01

To investigate the genetic diversity of the Plasmodium falciparum apical membrane antigen 1 (PfAMA1) gene in Southeast Asia, we determined PfAMA1 sequences from 135 field isolates collected from the China-Myanmar border area and compared them with 956 publically available PfAMA1 sequences from seven global P. falciparum populations. This analysis revealed high genetic diversity of PfAMA1 in global P. falciparum populations with a total of 229 haplotypes identified. The genetic diversity of PfAMA1 gene from the China-Myanmar border is not evenly distributed in the different domains of this gene. Sequence diversity in PfAMA1 from the China-Myanmar border is lower than that observed in Thai, African and Oceanian populations, but higher than that in the South American population. This appeared to correlate well with the levels of endemicity of different malaria-endemic regions, where hyperendemic regions favor genetic cross of the parasite isolates and generation of higher genetic diversity. Neutrality tests show significant departure from neutrality in the entire ectodomain and Domain I of PfAMA1 in the China-Myanmar border parasite population. We found evidence supporting a substantial continent-wise genetic structure among P. falciparum populations, with the highest genetic differentiation detected between the China-Myanmar border and the South American populations. Whereas no alleles were unique to a specific region, there were considerable geographical differences in major alleles and their frequencies, highlighting further necessity to include more PfAMA1 alleles in vaccine designs. Copyright © 2016 Elsevier B.V. All rights reserved.

Wildflower Plantings Do Not Compete With Neighboring Almond Orchards for Pollinator Visits.

PubMed

Lundin, Ola; Ward, Kimiora L; Artz, Derek R; Boyle, Natalie K; Pitts-Singer, Theresa L; Williams, Neal M

2017-06-01

The engineering of flowering agricultural field borders has emerged as a research and policy priority to mitigate threats to pollinators. Studies have, however, rarely addressed the potential that flowering field borders might compete with neighboring crops for pollinator visits if they both are in bloom at the same time, despite this being a concern expressed by growers. We evaluated how wildflower plantings added to orchard borders in a large (512 ha) commercial almond orchard affected honey bee and wild bee visitation to orchard borders and the crop. The study was conducted over two consecutive seasons using three large (0.48 ha) wildflower plantings paired with control orchard borders in a highly simplified agricultural landscape in California. Honey bee (Apis mellifera L.) and wild bee visitation to wildflower plots were at least an order of magnitude higher than to control plots, but increased honey bee visitation to wildflower plots did not lead to any detectable shifts in honey bee visitation to almond flowers in the neighboring orchard. Wild bees were rarely observed visiting almond flowers irrespective of border treatment, indicating a limited short-term potential for augmenting crop pollination using wild bees in highly simplified agricultural landscapes. Although further studies are warranted on bee visitation and crop yield from spatially independent orchards, this study indicates that growers can support bees with alternative forage in almond orchards without risking competition between the wildflower plantings and the crop. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The use of automated bioacoustic recorders to replace human wildlife surveys: an example using nightjars.

PubMed

Zwart, Mieke C; Baker, Andrew; McGowan, Philip J K; Whittingham, Mark J

2014-01-01

To be able to monitor and protect endangered species, we need accurate information on their numbers and where they live. Survey methods using automated bioacoustic recorders offer significant promise, especially for species whose behaviour or ecology reduces their detectability during traditional surveys, such as the European nightjar. In this study we examined the utility of automated bioacoustic recorders and the associated classification software as a way to survey for wildlife, using the nightjar as an example. We compared traditional human surveys with results obtained from bioacoustic recorders. When we compared these two methods using the recordings made at the same time as the human surveys, we found that recorders were better at detecting nightjars. However, in practice fieldworkers are likely to deploy recorders for extended periods to make best use of them. Our comparison of this practical approach with human surveys revealed that recorders were significantly better at detecting nightjars than human surveyors: recorders detected nightjars during 19 of 22 survey periods, while surveyors detected nightjars on only six of these occasions. In addition, there was no correlation between the amount of vocalisation captured by the acoustic recorders and the abundance of nightjars as recorded by human surveyors. The data obtained from the recorders revealed that nightjars were most active just before dawn and just after dusk, and least active during the middle of the night. As a result, we found that recording at both dusk and dawn or only at dawn would give reasonably high levels of detection while significantly reducing recording time, preserving battery life. Our analyses suggest that automated bioacoustic recorders could increase the detection of other species, particularly those that are known to be difficult to detect using traditional survey methods. The accuracy of detection is especially important when the data are used to inform conservation.

Evaluating detection and estimation capabilities of magnetometer-based vehicle sensors

NASA Astrophysics Data System (ADS)

Slater, David M.; Jacyna, Garry M.

2013-05-01

In an effort to secure the northern and southern United States borders, MITRE has been tasked with developing Modeling and Simulation (M&S) tools that accurately capture the mapping between algorithm-level Measures of Performance (MOP) and system-level Measures of Effectiveness (MOE) for current/future surveillance systems deployed by the the Customs and Border Protection Office of Technology Innovations and Acquisitions (OTIA). This analysis is part of a larger M&S undertaking. The focus is on two MOPs for magnetometer-based Unattended Ground Sensors (UGS). UGS are placed near roads to detect passing vehicles and estimate properties of the vehicle's trajectory such as bearing and speed. The first MOP considered is the probability of detection. We derive probabilities of detection for a network of sensors over an arbitrary number of observation periods and explore how the probability of detection changes when multiple sensors are employed. The performance of UGS is also evaluated based on the level of variance in the estimation of trajectory parameters. We derive the Cramer-Rao bounds for the variances of the estimated parameters in two cases: when no a priori information is known and when the parameters are assumed to be Gaussian with known variances. Sample results show that UGS perform significantly better in the latter case.

Design on wireless auto-measurement system for lead rail straightness measurement based on PSD

NASA Astrophysics Data System (ADS)

Yan, Xiugang; Zhang, Shuqin; Dong, Dengfeng; Cheng, Zhi; Wu, Guanghua; Wang, Jie; Zhou, Weihu

2016-10-01

Straightness detection is not only one of the key technologies for the product quality and installation accuracy of all types of lead rail, but also an important dimensional measurement technology. The straightness measuring devices now available have disadvantages of low automation level, limiting by measuring environment, and low measurement efficiency. In this paper, a wireless measurement system for straightness detection based on position sensitive detector (PSD) is proposed. The system has some advantage of high automation-level, convenient, high measurement efficiency, easy to transplanting and expanding, and can detect straightness of lead rail in real-time.

Defect analysis and detection of micro nano structured optical thin film

NASA Astrophysics Data System (ADS)

Xu, Chang; Shi, Nuo; Zhou, Lang; Shi, Qinfeng; Yang, Yang; Li, Zhuo

2017-10-01

This paper focuses on developing an automated method for detecting defects on our wavelength conversion thin film. We analyzes the operating principle of our wavelength conversion Micro/Nano thin film which absorbing visible light and emitting infrared radiation, indicates the relationship between the pixel's pattern and the radiation of the thin film, and issues the principle of defining blind pixels and their categories due to the calculated and experimental results. An effective method is issued for the automated detection based on wavelet transform and template matching. The results reveal that this method has desired accuracy and processing speed.

System for particle concentration and detection

DOEpatents

Morales, Alfredo M.; Whaley, Josh A.; Zimmerman, Mark D.; Renzi, Ronald F.; Tran, Huu M.; Maurer, Scott M.; Munslow, William D.

2013-03-19

A new microfluidic system comprising an automated prototype insulator-based dielectrophoresis (iDEP) triggering microfluidic device for pathogen monitoring that can eventually be run outside the laboratory in a real world environment has been used to demonstrate the feasibility of automated trapping and detection of particles. The system broadly comprised an aerosol collector for collecting air-borne particles, an iDEP chip within which to temporarily trap the collected particles and a laser and fluorescence detector with which to induce a fluorescence signal and detect a change in that signal as particles are trapped within the iDEP chip.

Automated and miniaturized detection of biological threats with a centrifugal microfluidic system

NASA Astrophysics Data System (ADS)

Mark, D.; van Oordt, T.; Strohmeier, O.; Roth, G.; Drexler, J.; Eberhard, M.; Niedrig, M.; Patel, P.; Zgaga-Griesz, A.; Bessler, W.; Weidmann, M.; Hufert, F.; Zengerle, R.; von Stetten, F.

2012-06-01

The world's growing mobility, mass tourism, and the threat of terrorism increase the risk of the fast spread of infectious microorganisms and toxins. Today's procedures for pathogen detection involve complex stationary devices, and are often too time consuming for a rapid and effective response. Therefore a robust and mobile diagnostic system is required. We present a microstructured LabDisk which performs complex biochemical analyses together with a mobile centrifugal microfluidic device which processes the LabDisk. This portable system will allow fully automated and rapid detection of biological threats at the point-of-need.

Petri net-based modelling of human-automation conflicts in aviation.

PubMed

Pizziol, Sergio; Tessier, Catherine; Dehais, Frédéric

2014-01-01

Analyses of aviation safety reports reveal that human-machine conflicts induced by poor automation design are remarkable precursors of accidents. A review of different crew-automation conflicting scenarios shows that they have a common denominator: the autopilot behaviour interferes with the pilot's goal regarding the flight guidance via 'hidden' mode transitions. Considering both the human operator and the machine (i.e. the autopilot or the decision functions) as agents, we propose a Petri net model of those conflicting interactions, which allows them to be detected as deadlocks in the Petri net. In order to test our Petri net model, we designed an autoflight system that was formally analysed to detect conflicting situations. We identified three conflicting situations that were integrated in an experimental scenario in a flight simulator with 10 general aviation pilots. The results showed that the conflicts that we had a-priori identified as critical had impacted the pilots' performance. Indeed, the first conflict remained unnoticed by eight participants and led to a potential collision with another aircraft. The second conflict was detected by all the participants but three of them did not manage the situation correctly. The last conflict was also detected by all the participants but provoked typical automation surprise situation as only one declared that he had understood the autopilot behaviour. These behavioural results are discussed in terms of workload and number of fired 'hidden' transitions. Eventually, this study reveals that both formal and experimental approaches are complementary to identify and assess the criticality of human-automation conflicts. Practitioner Summary: We propose a Petri net model of human-automation conflicts. An experiment was conducted with general aviation pilots performing a scenario involving three conflicting situations to test the soundness of our formal approach. This study reveals that both formal and experimental approaches are complementary to identify and assess the criticality conflicts.

Automated analysis of cell migration and nuclear envelope rupture in confined environments.

PubMed

Elacqua, Joshua J; McGregor, Alexandra L; Lammerding, Jan

2018-01-01

Recent in vitro and in vivo studies have highlighted the importance of the cell nucleus in governing migration through confined environments. Microfluidic devices that mimic the narrow interstitial spaces of tissues have emerged as important tools to study cellular dynamics during confined migration, including the consequences of nuclear deformation and nuclear envelope rupture. However, while image acquisition can be automated on motorized microscopes, the analysis of the corresponding time-lapse sequences for nuclear transit through the pores and events such as nuclear envelope rupture currently requires manual analysis. In addition to being highly time-consuming, such manual analysis is susceptible to person-to-person variability. Studies that compare large numbers of cell types and conditions therefore require automated image analysis to achieve sufficiently high throughput. Here, we present an automated image analysis program to register microfluidic constrictions and perform image segmentation to detect individual cell nuclei. The MATLAB program tracks nuclear migration over time and records constriction-transit events, transit times, transit success rates, and nuclear envelope rupture. Such automation reduces the time required to analyze migration experiments from weeks to hours, and removes the variability that arises from different human analysts. Comparison with manual analysis confirmed that both constriction transit and nuclear envelope rupture were detected correctly and reliably, and the automated analysis results closely matched a manual analysis gold standard. Applying the program to specific biological examples, we demonstrate its ability to detect differences in nuclear transit time between cells with different levels of the nuclear envelope proteins lamin A/C, which govern nuclear deformability, and to detect an increase in nuclear envelope rupture duration in cells in which CHMP7, a protein involved in nuclear envelope repair, had been depleted. The program thus presents a versatile tool for the study of confined migration and its effect on the cell nucleus.

77 FR 66635 - Notice Pursuant to the National Cooperative Research and Production Act of 1993-Border Security...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-06

..., Scottsdale, AZ; General Robotics, Sherman Oaks, CA; Global Technical Systems, Virginia Beach, VA; Hurley IR..., TX; Liquid Robotics, Sunnyvale, CA; Lockheed Martin Corporation, Gaithersburg, MD; Morpho Detection...

Despeckle filtering software toolbox for ultrasound imaging of the common carotid artery.

PubMed

Loizou, Christos P; Theofanous, Charoula; Pantziaris, Marios; Kasparis, Takis

2014-04-01

Ultrasound imaging of the common carotid artery (CCA) is a non-invasive tool used in medicine to assess the severity of atherosclerosis and monitor its progression through time. It is also used in border detection and texture characterization of the atherosclerotic carotid plaque in the CCA, the identification and measurement of the intima-media thickness (IMT) and the lumen diameter that all are very important in the assessment of cardiovascular disease (CVD). Visual perception, however, is hindered by speckle, a multiplicative noise, that degrades the quality of ultrasound B-mode imaging. Noise reduction is therefore essential for improving the visual observation quality or as a pre-processing step for further automated analysis, such as image segmentation of the IMT and the atherosclerotic carotid plaque in ultrasound images. In order to facilitate this preprocessing step, we have developed in MATLAB(®) a unified toolbox that integrates image despeckle filtering (IDF), texture analysis and image quality evaluation techniques to automate the pre-processing and complement the disease evaluation in ultrasound CCA images. The proposed software, is based on a graphical user interface (GUI) and incorporates image normalization, 10 different despeckle filtering techniques (DsFlsmv, DsFwiener, DsFlsminsc, DsFkuwahara, DsFgf, DsFmedian, DsFhmedian, DsFad, DsFnldif, DsFsrad), image intensity normalization, 65 texture features, 15 quantitative image quality metrics and objective image quality evaluation. The software is publicly available in an executable form, which can be downloaded from http://www.cs.ucy.ac.cy/medinfo/. It was validated on 100 ultrasound images of the CCA, by comparing its results with quantitative visual analysis performed by a medical expert. It was observed that the despeckle filters DsFlsmv, and DsFhmedian improved image quality perception (based on the expert's assessment and the image texture and quality metrics). It is anticipated that the system could help the physician in the assessment of cardiovascular image analysis. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Automated volumetry for unilateral hippocampal sclerosis detection in patients with temporal lobe epilepsy.

PubMed

Martins, Cristina; Moreira da Silva, Nadia; Silva, Guilherme; Rozanski, Verena E; Silva Cunha, Joao Paulo

2016-08-01

Hippocampal sclerosis (HS) is the most common cause of temporal lobe epilepsy (TLE) and can be identified in magnetic resonance imaging as hippocampal atrophy and subsequent volume loss. Detecting this kind of abnormalities through simple radiological assessment could be difficult, even for experienced radiologists. For that reason, hippocampal volumetry is generally used to support this kind of diagnosis. Manual volumetry is the traditional approach but it is time consuming and requires the physician to be familiar with neuroimaging software tools. In this paper, we propose an automated method, written as a script that uses FSL-FIRST, to perform hippocampal segmentation and compute an index to quantify hippocampi asymmetry (HAI). We compared the automated detection of HS (left or right) based on the HAI with the agreement of two experts in a group of 19 patients and 15 controls, achieving 84.2% sensitivity, 86.7% specificity and a Cohen's kappa coefficient of 0.704. The proposed method is integrated in the "Advanced Brain Imaging Lab" (ABrIL) cloud neurocomputing platform. The automated procedure is 77% (on average) faster to compute vs. the manual volumetry segmentation performed by an experienced physician.

Systems and methods for data quality control and cleansing

DOEpatents

Wenzel, Michael; Boettcher, Andrew; Drees, Kirk; Kummer, James

2016-05-31

A method for detecting and cleansing suspect building automation system data is shown and described. The method includes using processing electronics to automatically determine which of a plurality of error detectors and which of a plurality of data cleansers to use with building automation system data. The method further includes using processing electronics to automatically detect errors in the data and cleanse the data using a subset of the error detectors and a subset of the cleansers.

Functional Specifications to an Automated Retinal Scanner for Use in Plotting the Vascular Map

DTIC Science & Technology

1988-12-01

available an aid in the early detection and continuing treatment of diabetes . Therefore, it is the distinct wish of the author that this system provide some...choroid, it may be possible to detect diabetes earlier and stem the tide of retinopathy in those patients so afflicted. Additionally, retinal...Subject Terms (continue on reverse i necessary and identify t block number) Retinal Imaging, Automation, Infrared, Diabetic Retinopathy , Field I Group I

A Comprehensive Automated 3D Approach for Building Extraction, Reconstruction, and Regularization from Airborne Laser Scanning Point Clouds

PubMed Central

Dorninger, Peter; Pfeifer, Norbert

2008-01-01

Three dimensional city models are necessary for supporting numerous management applications. For the determination of city models for visualization purposes, several standardized workflows do exist. They are either based on photogrammetry or on LiDAR or on a combination of both data acquisition techniques. However, the automated determination of reliable and highly accurate city models is still a challenging task, requiring a workflow comprising several processing steps. The most relevant are building detection, building outline generation, building modeling, and finally, building quality analysis. Commercial software tools for building modeling require, generally, a high degree of human interaction and most automated approaches described in literature stress the steps of such a workflow individually. In this article, we propose a comprehensive approach for automated determination of 3D city models from airborne acquired point cloud data. It is based on the assumption that individual buildings can be modeled properly by a composition of a set of planar faces. Hence, it is based on a reliable 3D segmentation algorithm, detecting planar faces in a point cloud. This segmentation is of crucial importance for the outline detection and for the modeling approach. We describe the theoretical background, the segmentation algorithm, the outline detection, and the modeling approach, and we present and discuss several actual projects. PMID:27873931

Imported Plasmodium falciparum and locally transmitted Plasmodium vivax: cross-border malaria transmission scenario in northwestern Thailand.

PubMed

Sriwichai, Patchara; Karl, Stephan; Samung, Yudthana; Kiattibutr, Kirakorn; Sirichaisinthop, Jeeraphat; Mueller, Ivo; Cui, Liwang; Sattabongkot, Jetsumon

2017-06-21

Cross-border malaria transmission is an important problem for national malaria control programmes. The epidemiology of cross-border malaria is further complicated in areas where Plasmodium falciparum and Plasmodium vivax are both endemic. By combining passive case detection data with entomological data, a transmission scenario on the northwestern Thai-Myanmar border where P. falciparum is likely driven by importation was described, whereas P. vivax is also locally transmitted. This study highlights the differences in the level of control required to eliminate P. falciparum and P. vivax from the same region. Malaria case data were collected from malaria clinics in Suan Oi village, Tak Province, Thailand between 2011 and 2014. Infections were diagnosed by light microscopy. Demographic data, including migrant status, were correlated with concomitantly collected entomology data from 1330 mosquito trap nights using logistic regression. Malaria infection in the captured mosquitoes was detected by ELISA. Recent migrants were almost four times more likely to be infected with P. falciparum compared with Thai patients (OR 3.84, p < 0.001) and cases were significantly associated with seasonal migration. However, P. falciparum infection was not associated with the Anopheles mosquito capture rates, suggesting predominantly imported infections. In contrast, recent migrants were equally likely to present with P. vivax as mid-term migrants. Both migrant groups were twice as likely to be infected with P. vivax in comparison to the resident Thai population (OR 1.96, p < 0.001 and OR 1.94, p < 0.001, respectively). Plasmodium vivax cases were strongly correlated with age and local capture rates of two major vector species Anopheles minimus and Anopheles maculatus (OR 1.23, p = 0.020 and OR 1.33, p = 0.046, respectively), suggesting that a high level of local transmission might be causing these infections. On the Thai-Myanmar border, P. falciparum infections occur mostly in the recent migrant population with a seasonality reflecting that of agricultural activity, rather than that of the local mosquito population. This suggests that P. falciparum was mostly imported. In contrast, P. vivax cases were significantly associated with mosquito capture rates and less with migrant status, indicating local transmission. This highlights the different timelines and requirements for P. falciparum and P. vivax elimination in the same region and underlines the importance of multinational, cross-border malaria control.

Glaucoma risk index: automated glaucoma detection from color fundus images.

PubMed

Bock, Rüdiger; Meier, Jörg; Nyúl, László G; Hornegger, Joachim; Michelson, Georg

2010-06-01

Glaucoma as a neurodegeneration of the optic nerve is one of the most common causes of blindness. Because revitalization of the degenerated nerve fibers of the optic nerve is impossible early detection of the disease is essential. This can be supported by a robust and automated mass-screening. We propose a novel automated glaucoma detection system that operates on inexpensive to acquire and widely used digital color fundus images. After a glaucoma specific preprocessing, different generic feature types are compressed by an appearance-based dimension reduction technique. Subsequently, a probabilistic two-stage classification scheme combines these features types to extract the novel Glaucoma Risk Index (GRI) that shows a reasonable glaucoma detection performance. On a sample set of 575 fundus images a classification accuracy of 80% has been achieved in a 5-fold cross-validation setup. The GRI gains a competitive area under ROC (AUC) of 88% compared to the established topography-based glaucoma probability score of scanning laser tomography with AUC of 87%. The proposed color fundus image-based GRI achieves a competitive and reliable detection performance on a low-priced modality by the statistical analysis of entire images of the optic nerve head. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Focused ultrasound: concept for automated transcutaneous control of hemorrhage in austere settings.

PubMed

Kucewicz, John C; Bailey, Michael R; Kaczkowski, Peter J; Carter, Stephen J

2009-04-01

High intensity focused ultrasound (HIFU) is being developed for a range of clinical applications. Of particular interest to NASA and the military is the use of HIFU for traumatic injuries because HIFU has the unique ability to transcutaneously stop bleeding. Automation of this technology would make possible its use in remote, austere settings by personnel not specialized in medical ultrasound. Here a system to automatically detect and target bleeding is tested and reported. The system uses Doppler ultrasound images from a clinical ultrasound scanner for bleeding detection and hardware for HIFU therapy. The system was tested using a moving string to simulate blood flow and targeting was visualized by Schlieren imaging to show the focusing of the HIFU acoustic waves. When instructed by the operator, a Doppler ultrasound image is acquired and processed to detect and localize the moving string, and the focus of the HIFU array is electronically adjusted to target the string. Precise and accurate targeting was verified in the Schlieren images. An automated system to detect and target simulated bleeding has been built and tested. The system could be combined with existing algorithms to detect, target, and treat clinical bleeding.

Automation for deep space vehicle monitoring

NASA Technical Reports Server (NTRS)

Schwuttke, Ursula M.

1991-01-01

Information on automation for deep space vehicle monitoring is given in viewgraph form. Information is given on automation goals and strategy; the Monitor Analyzer of Real-time Voyager Engineering Link (MARVEL); intelligent input data management; decision theory for making tradeoffs; dynamic tradeoff evaluation; evaluation of anomaly detection results; evaluation of data management methods; system level analysis with cooperating expert systems; the distributed architecture of multiple expert systems; and event driven response.

Automated Power-Distribution System

NASA Technical Reports Server (NTRS)

Thomason, Cindy; Anderson, Paul M.; Martin, James A.

1990-01-01

Automated power-distribution system monitors and controls electrical power to modules in network. Handles both 208-V, 20-kHz single-phase alternating current and 120- to 150-V direct current. Power distributed to load modules from power-distribution control units (PDCU's) via subsystem distributors. Ring busses carry power to PDCU's from power source. Needs minimal attention. Detects faults and also protects against them. Potential applications include autonomous land vehicles and automated industrial process systems.

a Novel Method for Automation of 3d Hydro Break Line Generation from LIDAR Data Using Matlab

NASA Astrophysics Data System (ADS)

Toscano, G. J.; Gopalam, U.; Devarajan, V.

2013-08-01

Water body detection is necessary to generate hydro break lines, which are in turn useful in creating deliverables such as TINs, contours, DEMs from LiDAR data. Hydro flattening follows the detection and delineation of water bodies (lakes, rivers, ponds, reservoirs, streams etc.) with hydro break lines. Manual hydro break line generation is time consuming and expensive. Accuracy and processing time depend on the number of vertices marked for delineation of break lines. Automation with minimal human intervention is desired for this operation. This paper proposes using a novel histogram analysis of LiDAR elevation data and LiDAR intensity data to automatically detect water bodies. Detection of water bodies using elevation information was verified by checking against LiDAR intensity data since the spectral reflectance of water bodies is very small compared with that of land and vegetation in near infra-red wavelength range. Detection of water bodies using LiDAR intensity data was also verified by checking against LiDAR elevation data. False detections were removed using morphological operations and 3D break lines were generated. Finally, a comparison of automatically generated break lines with their semi-automated/manual counterparts was performed to assess the accuracy of the proposed method and the results were discussed.

Detection of lobular structures in normal breast tissue.

PubMed

Apou, Grégory; Schaadt, Nadine S; Naegel, Benoît; Forestier, Germain; Schönmeyer, Ralf; Feuerhake, Friedrich; Wemmert, Cédric; Grote, Anne

2016-07-01

Ongoing research into inflammatory conditions raises an increasing need to evaluate immune cells in histological sections in biologically relevant regions of interest (ROIs). Herein, we compare different approaches to automatically detect lobular structures in human normal breast tissue in digitized whole slide images (WSIs). This automation is required to perform objective and consistent quantitative studies on large data sets. In normal breast tissue from nine healthy patients immunohistochemically stained for different markers, we evaluated and compared three different image analysis methods to automatically detect lobular structures in WSIs: (1) a bottom-up approach using the cell-based data for subsequent tissue level classification, (2) a top-down method starting with texture classification at tissue level analysis of cell densities in specific ROIs, and (3) a direct texture classification using deep learning technology. All three methods result in comparable overall quality allowing automated detection of lobular structures with minor advantage in sensitivity (approach 3), specificity (approach 2), or processing time (approach 1). Combining the outputs of the approaches further improved the precision. Different approaches of automated ROI detection are feasible and should be selected according to the individual needs of biomarker research. Additionally, detected ROIs could be used as a basis for quantification of immune infiltration in lobular structures. Copyright © 2016 Elsevier Ltd. All rights reserved.

Actuation of chitosan-aptamer nanobrush borders for pathogen sensing.

PubMed

Hills, Katherine D; Oliveira, Daniela A; Cavallaro, Nicholas D; Gomes, Carmen L; McLamore, Eric S

2018-03-26

We demonstrate a sensing mechanism for rapid detection of Listeria monocytogenes in food samples using the actuation of chitosan-aptamer nanobrush borders. The bio-inspired soft material and sensing strategy mimic natural symbiotic systems, where low levels of bacteria are selectively captured from complex matrices. To engineer this biomimetic system, we first develop reduced graphene oxide/nanoplatinum (rGO-nPt) electrodes, and characterize the fundamental electrochemical behavior in the presence and absence of chitosan nanobrushes during actuation (pH-stimulated osmotic swelling). We then characterize the electrochemical behavior of the nanobrush when receptors (antibodies or DNA aptamers) are conjugated to the surface. Finally, we test various techniques to determine the most efficient capture strategy based on nanobrush actuation, and then apply the biosensors in a food product. Maximum cell capture occurs when aptamers conjugated to the nanobrush bind cells in the extended conformation (pH < 6), followed by impedance measurement in the collapsed nanobrush conformation (pH > 6). The aptamer-nanobrush hybrid material was more efficient than the antibody-nanobrush material, which was likely due to the relatively high adsorption capacity for aptamers. The biomimetic material was used to develop a rapid test (17 min) for selectively detecting L. monocytogenes at concentrations ranging from 9 to 107 CFU mL-1 with no pre-concentration, and in the presence of other Gram-positive cells (Listeria innocua and Staphylococcus aureus). Use of this bio-inspired material is among the most efficient for L. monocytogenes sensing to date, and does not require sample pretreatment, making nanobrush borders a promising new material for rapid pathogen detection in food.

Challenges to natural resource monitoring in a small border park: terrestrial mammals at Coronado National Memorial, Cochise County, Arizona

USGS Publications Warehouse

Swann, Don E.; Bucci, Melanie; Kuenzi, Amy J.; Alberti, Barbara N.; Schwalbe, Cecil R.; Halvorson, William L.; van Riper, Charles; Schwalbe, Cecil R.

2010-01-01

Long-term monitoring in national parks is essential to meet National Park Service and other important public goals. Terrestrial mammals are often proposed for monitoring because large mammals are of interest to visitors and small mammals are important as prey. However, traditional monitoring strategies for mammals are often too expensive and complex to sustain for long periods, particularly in small parks. To evaluate potential strategies for long-term monitoring in small parks, we conducted an intensive one-year inventory of terrestrial mammals at Coronado National Memorial, located in Arizona on the U.S.-Mexico international border, then continued less-intensive monitoring at the site for 7 additional years. During 1996-2003 we confirmed 44 species of terrestrial mammals. Most species (40) were detected in the intensive first year of the study, but we continued to detect new species in later years. Mark-recapture data on small mammals indicated large inter-annual fluctuations in population size, but no significant trend over the 7-year period. Issues associated with the international border affected monitoring efforts and increased sampling costs. Our study confirms that sustained annual monitoring of mammals is probably not feasible in small park units like Coronado. However, comparisons of our data with past studies provide insight into important changes in the mammal community since the 1970s, including an increase in abundance and diversity of grassland rodents. Our results suggest that intensive inventories every 10-20 years may be a valuable and cost-effective approach for detecting long-term trends in terrestrial mammal communities in small natural areas.

Automated Information System (AIS) Alarm System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hunteman, W.

1997-05-01

The Automated Information Alarm System is a joint effort between Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and Sandia National Laboratory to demonstrate and implement, on a small-to-medium sized local area network, an automated system that detects and automatically responds to attacks that use readily available tools and methodologies. The Alarm System will sense or detect, assess, and respond to suspicious activities that may be detrimental to information on the network or to continued operation of the network. The responses will allow stopping, isolating, or ejecting the suspicious activities. The number of sensors, the sensitivity of the sensors, themore » assessment criteria, and the desired responses may be set by the using organization to meet their local security policies.« less

Automatic nipple detection on 3D images of an automated breast ultrasound system (ABUS)

NASA Astrophysics Data System (ADS)

Javanshir Moghaddam, Mandana; Tan, Tao; Karssemeijer, Nico; Platel, Bram

2014-03-01

Recent studies have demonstrated that applying Automated Breast Ultrasound in addition to mammography in women with dense breasts can lead to additional detection of small, early stage breast cancers which are occult in corresponding mammograms. In this paper, we proposed a fully automatic method for detecting the nipple location in 3D ultrasound breast images acquired from Automated Breast Ultrasound Systems. The nipple location is a valuable landmark to report the position of possible abnormalities in a breast or to guide image registration. To detect the nipple location, all images were normalized. Subsequently, features have been extracted in a multi scale approach and classification experiments were performed using a gentle boost classifier to identify the nipple location. The method was applied on a dataset of 100 patients with 294 different 3D ultrasound views from Siemens and U-systems acquisition systems. Our database is a representative sample of cases obtained in clinical practice by four medical centers. The automatic method could accurately locate the nipple in 90% of AP (Anterior-Posterior) views and in 79% of the other views.

Automated processing integrated with a microflow cytometer for pathogen detection in clinical matrices

PubMed Central

Golden, J.P.; Verbarg, J.; Howell, P.B.; Shriver-Lake, L.C.; Ligler, F.S.

2012-01-01

A spinning magnetic trap (MagTrap) for automated sample processing was integrated with a microflow cytometer capable of simultaneously detecting multiple targets to provide an automated sample-to-answer diagnosis in 40 min. After target capture on fluorescently coded magnetic microspheres, the magnetic trap automatically concentrated the fluorescently coded microspheres, separated the captured target from the sample matrix, and exposed the bound target sequentially to biotinylated tracer molecules and streptavidin-labeled phycoerythrin. The concentrated microspheres were then hydrodynamically focused in a microflow cytometer capable of 4-color analysis (two wavelengths for microsphere identification, one for light scatter to discriminate single microspheres and one for phycoerythrin bound to the target). A three-fold decrease in sample preparation time and an improved detection limit, independent of target preconcentration, was demonstrated for detection of Escherichia coli 0157:H7 using the MagTrap as compared to manual processing. Simultaneous analysis of positive and negative controls, along with the assay reagents specific for the target, was used to obtain dose–response curves, demonstrating the potential for quantification of pathogen load in buffer and serum. PMID:22960010

Automated processing integrated with a microflow cytometer for pathogen detection in clinical matrices.

PubMed

Golden, J P; Verbarg, J; Howell, P B; Shriver-Lake, L C; Ligler, F S

2013-02-15

A spinning magnetic trap (MagTrap) for automated sample processing was integrated with a microflow cytometer capable of simultaneously detecting multiple targets to provide an automated sample-to-answer diagnosis in 40 min. After target capture on fluorescently coded magnetic microspheres, the magnetic trap automatically concentrated the fluorescently coded microspheres, separated the captured target from the sample matrix, and exposed the bound target sequentially to biotinylated tracer molecules and streptavidin-labeled phycoerythrin. The concentrated microspheres were then hydrodynamically focused in a microflow cytometer capable of 4-color analysis (two wavelengths for microsphere identification, one for light scatter to discriminate single microspheres and one for phycoerythrin bound to the target). A three-fold decrease in sample preparation time and an improved detection limit, independent of target preconcentration, was demonstrated for detection of Escherichia coli 0157:H7 using the MagTrap as compared to manual processing. Simultaneous analysis of positive and negative controls, along with the assay reagents specific for the target, was used to obtain dose-response curves, demonstrating the potential for quantification of pathogen load in buffer and serum. Published by Elsevier B.V.

Advances toward fully automated in vivo assessment of oral epithelial dysplasia by nuclear endomicroscopy-A pilot study.

PubMed

Liese, Jan; Winter, Karsten; Glass, Änne; Bertolini, Julia; Kämmerer, Peer Wolfgang; Frerich, Bernhard; Schiefke, Ingolf; Remmerbach, Torsten W

2017-11-01

Uncertainties in detection of oral epithelial dysplasia (OED) frequently result from sampling error especially in inflammatory oral lesions. Endomicroscopy allows non-invasive, "en face" imaging of upper oral epithelium, but parameters of OED are unknown. Mucosal nuclei were imaged in 34 toluidine blue-stained oral lesions with a commercial endomicroscopy. Histopathological diagnosis showed four biopsies in "dys-/neoplastic," 23 in "inflammatory," and seven in "others" disease groups. Strength of different assessment strategies of nuclear scoring, nuclear count, and automated nuclear analysis were measured by area under ROC curve (AUC) to identify histopathological "dys-/neoplastic" group. Nuclear objects from automated image analysis were visually corrected. Best-performing parameters of nuclear-to-image ratios were the count of large nuclei (AUC=0.986) and 6-nearest neighborhood relation (AUC=0.896), and best parameters of nuclear polymorphism were the count of atypical nuclei (AUC=0.996) and compactness of nuclei (AUC=0.922). Excluding low-grade OED, nuclear scoring and count reached 100% sensitivity and 98% specificity for detection of dys-/neoplastic lesions. In automated analysis, combination of parameters enhanced diagnostic strength. Sensitivity of 100% and specificity of 87% were seen for distances of 6-nearest neighbors and aspect ratios even in uncorrected objects. Correction improved measures of nuclear polymorphism only. The hue of background color was stronger than nuclear density (AUC=0.779 vs 0.687) to detect dys-/neoplastic group indicating that macroscopic aspect is biased. Nuclear-to-image ratios are applicable for automated optical in vivo diagnostics for oral potentially malignant disorders. Nuclear endomicroscopy may promote non-invasive, early detection of dys-/neoplastic lesions by reducing sampling error. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Testing the effectiveness of automated acoustic sensors for monitoring vocal activity of Marbled Murrelets Brachyramphus marmoratus

USGS Publications Warehouse

Cragg, Jenna L.; Burger, Alan E.; Piatt, John F.

2015-01-01

Cryptic nest sites and secretive breeding behavior make population estimates and monitoring of Marbled Murrelets Brachyramphus marmoratus difficult and expensive. Standard audio-visual and radar protocols have been refined but require intensive field time by trained personnel. We examined the detection range of automated sound recorders (Song Meters; Wildlife Acoustics Inc.) and the reliability of automated recognition models (“recognizers”) for identifying and quantifying Marbled Murrelet vocalizations during the 2011 and 2012 breeding seasons at Kodiak Island, Alaska. The detection range of murrelet calls by Song Meters was estimated to be 60 m. Recognizers detected 20 632 murrelet calls (keer and keheer) from a sample of 268 h of recordings, yielding 5 870 call series, which compared favorably with human scanning of spectrograms (on average detecting 95% of the number of call series identified by a human observer, but not necessarily the same call series). The false-negative rate (percentage of murrelet call series that the recognizers failed to detect) was 32%, mainly involving weak calls and short call series. False-positives (other sounds included by recognizers as murrelet calls) were primarily due to complex songs of other bird species, wind and rain. False-positives were lower in forest nesting habitat (48%) and highest in shrubby vegetation where calls of other birds were common (97%–99%). Acoustic recorders tracked spatial and seasonal trends in vocal activity, with higher call detections in high-quality forested habitat and during late July/early August. Automated acoustic monitoring of Marbled Murrelet calls could provide cost-effective, valuable information for assessing habitat use and temporal and spatial trends in nesting activity; reliability is dependent on careful placement of sensors to minimize false-positives and on prudent application of digital recognizers with visual checking of spectrograms.

Automated Detection of Clinically Significant Prostate Cancer in mp-MRI Images Based on an End-to-End Deep Neural Network.

PubMed

Wang, Zhiwei; Liu, Chaoyue; Cheng, Danpeng; Wang, Liang; Yang, Xin; Cheng, Kwang-Ting

2018-05-01

Automated methods for detecting clinically significant (CS) prostate cancer (PCa) in multi-parameter magnetic resonance images (mp-MRI) are of high demand. Existing methods typically employ several separate steps, each of which is optimized individually without considering the error tolerance of other steps. As a result, they could either involve unnecessary computational cost or suffer from errors accumulated over steps. In this paper, we present an automated CS PCa detection system, where all steps are optimized jointly in an end-to-end trainable deep neural network. The proposed neural network consists of concatenated subnets: 1) a novel tissue deformation network (TDN) for automated prostate detection and multimodal registration and 2) a dual-path convolutional neural network (CNN) for CS PCa detection. Three types of loss functions, i.e., classification loss, inconsistency loss, and overlap loss, are employed for optimizing all parameters of the proposed TDN and CNN. In the training phase, the two nets mutually affect each other and effectively guide registration and extraction of representative CS PCa-relevant features to achieve results with sufficient accuracy. The entire network is trained in a weakly supervised manner by providing only image-level annotations (i.e., presence/absence of PCa) without exact priors of lesions' locations. Compared with most existing systems which require supervised labels, e.g., manual delineation of PCa lesions, it is much more convenient for clinical usage. Comprehensive evaluation based on fivefold cross validation using 360 patient data demonstrates that our system achieves a high accuracy for CS PCa detection, i.e., a sensitivity of 0.6374 and 0.8978 at 0.1 and 1 false positives per normal/benign patient.

Automated detection and differentiation of drusen, exudates, and cotton-wool spots in digital color fundus photographs for diabetic retinopathy diagnosis.

PubMed

Niemeijer, Meindert; van Ginneken, Bram; Russell, Stephen R; Suttorp-Schulten, Maria S A; Abràmoff, Michael D

2007-05-01

To describe and evaluate a machine learning-based, automated system to detect exudates and cotton-wool spots in digital color fundus photographs and differentiate them from drusen, for early diagnosis of diabetic retinopathy. Three hundred retinal images from one eye of 300 patients with diabetes were selected from a diabetic retinopathy telediagnosis database (nonmydriatic camera, two-field photography): 100 with previously diagnosed bright lesions and 200 without. A machine learning computer program was developed that can identify and differentiate among drusen, (hard) exudates, and cotton-wool spots. A human expert standard for the 300 images was obtained by consensus annotation by two retinal specialists. Sensitivities and specificities of the annotations on the 300 images by the automated system and a third retinal specialist were determined. The system achieved an area under the receiver operating characteristic (ROC) curve of 0.95 and sensitivity/specificity pairs of 0.95/0.88 for the detection of bright lesions of any type, and 0.95/0.86, 0.70/0.93, and 0.77/0.88 for the detection of exudates, cotton-wool spots, and drusen, respectively. The third retinal specialist achieved pairs of 0.95/0.74 for bright lesions and 0.90/0.98, 0.87/0.98, and 0.92/0.79 per lesion type. A machine learning-based, automated system capable of detecting exudates and cotton-wool spots and differentiating them from drusen in color images obtained in community based diabetic patients has been developed and approaches the performance level of retinal experts. If the machine learning can be improved with additional training data sets, it may be useful for detecting clinically important bright lesions, enhancing early diagnosis, and reducing visual loss in patients with diabetes.

A Self-Adapting System for the Automated Detection of Inter-Ictal Epileptiform Discharges

PubMed Central

Lodder, Shaun S.; van Putten, Michel J. A. M.

2014-01-01

Purpose Scalp EEG remains the standard clinical procedure for the diagnosis of epilepsy. Manual detection of inter-ictal epileptiform discharges (IEDs) is slow and cumbersome, and few automated methods are used to assist in practice. This is mostly due to low sensitivities, high false positive rates, or a lack of trust in the automated method. In this study we aim to find a solution that will make computer assisted detection more efficient than conventional methods, while preserving the detection certainty of a manual search. Methods Our solution consists of two phases. First, a detection phase finds all events similar to epileptiform activity by using a large database of template waveforms. Individual template detections are combined to form “IED nominations”, each with a corresponding certainty value based on the reliability of their contributing templates. The second phase uses the ten nominations with highest certainty and presents them to the reviewer one by one for confirmation. Confirmations are used to update certainty values of the remaining nominations, and another iteration is performed where ten nominations with the highest certainty are presented. This continues until the reviewer is satisfied with what has been seen. Reviewer feedback is also used to update template accuracies globally and improve future detections. Key Findings Using the described method and fifteen evaluation EEGs (241 IEDs), one third of all inter-ictal events were shown after one iteration, half after two iterations, and 74%, 90%, and 95% after 5, 10 and 15 iterations respectively. Reviewing fifteen iterations for the 20–30 min recordings 1took approximately 5 min. Significance The proposed method shows a practical approach for combining automated detection with visual searching for inter-ictal epileptiform activity. Further evaluation is needed to verify its clinical feasibility and measure the added value it presents. PMID:24454813

Automated image-based colon cleansing for laxative-free CT colonography computer-aided polyp detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Linguraru, Marius George; Panjwani, Neil; Fletcher, Joel G.

2011-12-15

Purpose: To evaluate the performance of a computer-aided detection (CAD) system for detecting colonic polyps at noncathartic computed tomography colonography (CTC) in conjunction with an automated image-based colon cleansing algorithm. Methods: An automated colon cleansing algorithm was designed to detect and subtract tagged-stool, accounting for heterogeneity and poor tagging, to be used in conjunction with a colon CAD system. The method is locally adaptive and combines intensity, shape, and texture analysis with probabilistic optimization. CTC data from cathartic-free bowel preparation were acquired for testing and training the parameters. Patients underwent various colonic preparations with barium or Gastroview in divided dosesmore » over 48 h before scanning. No laxatives were administered and no dietary modifications were required. Cases were selected from a polyp-enriched cohort and included scans in which at least 90% of the solid stool was visually estimated to be tagged and each colonic segment was distended in either the prone or supine view. The CAD system was run comparatively with and without the stool subtraction algorithm. Results: The dataset comprised 38 CTC scans from prone and/or supine scans of 19 patients containing 44 polyps larger than 10 mm (22 unique polyps, if matched between prone and supine scans). The results are robust on fine details around folds, thin-stool linings on the colonic wall, near polyps and in large fluid/stool pools. The sensitivity of the CAD system is 70.5% per polyp at a rate of 5.75 false positives/scan without using the stool subtraction module. This detection improved significantly (p = 0.009) after automated colon cleansing on cathartic-free data to 86.4% true positive rate at 5.75 false positives/scan. Conclusions: An automated image-based colon cleansing algorithm designed to overcome the challenges of the noncathartic colon significantly improves the sensitivity of colon CAD by approximately 15%.« less

Evaluation of Exposures to Diesel Particulate Matter Utilizing Ambient Air Monitoring and Urinary Biomarkers Among Pedestrian Commuters who Cross the U.S.-Mexico Border at San Ysidro, CA

NASA Astrophysics Data System (ADS)

Galaviz, Vanessa Eileen

Background: Walk-in-line pedestrians crossing the U.S.-Mexico border northbound at the San Ysidro, CA Port of Entry ("Border Commuters") may be at an increased risk of experiencing elevated traffic-related air pollution, including diesel exhaust (DE). DE exposure has been associated with numerous adverse health effects, particularly cardiovascular and respiratory problems, including as lung cancer. Pedestrian crossers wait in line for extended periods and stand within 10 feet of highly concentrated traffic, particularly to diesel buses. Understanding the magnitude of traffic-related exposures is important for this vulnerable population. It was hypothesized that subjects who reside in Tijuana, Baja California, Mexico and cross the border as a pedestrian will experience higher exposure to traffic-related pollutants than those who live and work in South San Diego, CA, USA and do not cross the border. Methods: Ninety-one participants were enrolled for this study; 80% were "Border Commuters" and 20% were "Non-Border Commuters". "Non-Border Commuters" served as the comparison group and were defined as residents who lived in or near and worked or went to school in San Ysidro, CA but did not cross the border. Questionnaires, time activity diaries, and urine samples were collected from all participants. Of the "Border Commuters", 56 personal 24-hour PM2.5 and 1-nitropyrene (1-NP) - a marker for diesel exhaust - samples were collected. There were 22 at-home indoor and 14 at-home outdoor 1-NP samples collected. Additionally, area samples collected at the border included 35 days of 1-NP, black carbon (BC), carbon monoxide (CO), fine particulate matter (PM2.5) and ultrafine particulate matter (UFP). Of the "Non-Border Commuters", 15 personal 24-hour PM2.5 and 1-NP samples were collected. Additonally, 3 at-home indoor and outdoor 24-hour 1-NP samples were collected. Results: Personal exposure to PM2.5 was nearly 2-fold higher among "Border Commuters" compared to "Non-Border Commuters" (39 +/- 30 μg/m3 vs 21 +/- 11 μg/m3), while personal exposure to 1-NP was more than 8-fold higher among the "Border Commuters"(1.7 +/- 2.6 vs 0.22 +/- 0.21 pg/m3, p<0.01, Mann-Whitney). Two metabolites of 1-NP were readily detected in urine samples, the most abundant of which was 8-hydroxy-1-nitropyrene (8-OHNP). "Border Commuters" had greater than a 2-fold higher concentration of 8-OHNP (0.071 +/- 0.066 vs 0.032 +/- 0.021 pg/mL, p=0.05, Mann-Whitney) and a 3-fold higher concentration of 8-OHNAAP (0.063 +/- 0.11 vs 0.021 +/- 0.013 pg/mL, p=0.11, Mann-Whitney) as compared to "Non-Border Commuters". Home indoor concentrations of 1-NP were 30-60% of home outdoor concentrations with "Border Commuters" having higher concentrations both indoors (0.64 +/- 0.81 vs 0.078 +/- 0.075 pg/m3, p=0.04, Mann-Whitney) and outdoors (1.0 +/- 0.93 vs 0.27 +/- 0.24 pg/m3, p=0.11, Mann-Whitney) compared to "Non-Border Commuters". Border concentrations of 1-NP weighted by the time spent at the border, total travel given season, and season were all predictors of personal exposure to 1-NP among "Border Commuters". However, when placed in a multivariate linear regression model total travel given season was the only predictor variable to remain significant. Season was the only predictor for personal exposure to PM2.5 among "Border Commuters". Total travel was also a significant predictor for 8-OHNP among "Border Commuters." Median values (IQR) of daily averages for fixed-site measurements made at the border were as follows: 40,000 (24,000-52,000) UFP/cm3, 5 (3-6) ppm CO, 1.3 (0.5-2.6) pg/m3 1-NP, 4 (3-11) μg/m3 BC, 41 (23-57) μg/m3 real-time PM2.5, and 15 (13-22) μg/m3 gravimetric PM2.5. Wind speed was a predictor of gravimetric PM2.5 at the border explaining 22% of the variance. Relative humidity and vehicle delay were both predictors of UFP measured at the border, explaining 13% and 21% of the variance, respectively. However, when modeled together none remain significant. There were no predictors for 1-NP measurements at the border. Conclusions: This is the first quantitative study characterizing traffic-related exposure to a vulnerable population, indicating that this vulnerable population is indeed at high risk for exposure. "Border Commuters" experience higher exposure to 1-NP and PM2.5 as compared to "Non-Border Commuters", as determined by both personal and at-home measurements. In addition, traffic-related air pollution exposure among "Border Commuters" within 10 feet of highly concentrated traffic is of great public health concern as concentrations at the border are similar to near-roadway studies that link exposure to adverse health effects. Interventions to reduce border wait times would significantly reduce traffic pollutant exposures in this vulnerable population. However, further work needs to be done to understand the spatial heterogeneity of at-home exposures between the two study groups.

Collaborative Point Paper on Border Surveillance Technology

DTIC Science & Technology

2007-06-01

Systems PLC LORHIS (Long Range Hyperspectral Imaging System ) can be configured for either manned or unmanned aircraft to automatically detect and...Airships, and/or Aerostats, (RF, Electro-Optical, Infrared, Video) • Land- based Sensor Systems (Attended/Mobile and Unattended: e.g., CCD, Motion, Acoustic...electronic surveillance technologies for intrusion detection and warning. These ground- based systems are primarily short-range, up to around 500 meters

Procedure for Automated Eddy Current Crack Detection in Thin Titanium Plates

NASA Technical Reports Server (NTRS)

Wincheski, Russell A.

2012-01-01

This procedure provides the detailed instructions for conducting Eddy Current (EC) inspections of thin (5-30 mils) titanium membranes with thickness and material properties typical of the development of Ultra-Lightweight diaphragm Tanks Technology (ULTT). The inspection focuses on the detection of part-through, surface breaking fatigue cracks with depths between approximately 0.002" and 0.007" and aspect ratios (a/c) of 0.2-1.0 using an automated eddy current scanning and image processing technique.

Automated accident detection at intersections.

DOT National Transportation Integrated Search

2004-03-01

This research aims to provide a timely and accurate accident detection method at intersections, which is : very important for the Traffic Management System(TMS). This research uses acoustic signals to detect : accident at intersections. A system is c...

Automation in future air traffic management: effects of decision aid reliability on controller performance and mental workload.

PubMed

Metzger, Ulla; Parasuraman, Raja

2005-01-01

Future air traffic management concepts envisage shared decision-making responsibilities between controllers and pilots, necessitating that controllers be supported by automated decision aids. Even as automation tools are being introduced, however, their impact on the air traffic controller is not well understood. The present experiments examined the effects of an aircraft-to-aircraft conflict decision aid on performance and mental workload of experienced, full-performance level controllers in a simulated Free Flight environment. Performance was examined with both reliable (Experiment 1) and inaccurate automation (Experiment 2). The aid improved controller performance and reduced mental workload when it functioned reliably. However, detection of a particular conflict was better under manual conditions than under automated conditions when the automation was imperfect. Potential or actual applications of the results include the design of automation and procedures for future air traffic control systems.

Automated Monitoring of Pipeline Rights-of-Way

NASA Technical Reports Server (NTRS)

Frost, Chard Ritchie

2010-01-01

NASA Ames Research Center and the Pipeline Research Council International, Inc. have partnered in the formation of a research program to identify and develop the key technologies required to enable automated detection of threats to gas and oil transmission and distribution pipelines. This presentation describes the Right-of-way Automated Monitoring (RAM) program and highlights research successes to date, continuing challenges to implementing the RAM objectives, and the program's ongoing work and plans.

Improved Cloud Detection Utilizing Defense Meteorological Satellite Program near Infrared Measurements

DTIC Science & Technology

1982-01-27

Visible 3. 3 Ea r th Location, Colocation, and Normalization 4. IMAGE ANALYSIS 4. 1 Interactive Capabilities 4.2 Examples 5. AUTOMATED CLOUD...computer Interactive Data Access System (McIDAS) before image analysis and algorithm development were done. Earth-location is an automated procedure to...the factor l / s in (SSE) toward the gain settings given in Table 5. 4. IMAGE ANALYSIS 4.1 Interactive Capabilities The development of automated

Machine-vision-based roadway health monitoring and assessment : development of a shape-based pavement-crack-detection approach.

DOT National Transportation Integrated Search

2016-01-01

State highway agencies (SHAs) routinely employ semi-automated and automated image-based methods for network-level : pavement-cracking data collection, and there are different types of pavement-cracking data collected by SHAs for reporting and : manag...

Decision Making In A High-Tech World: Automation Bias and Countermeasures

NASA Technical Reports Server (NTRS)

Mosier, Kathleen L.; Skitka, Linda J.; Burdick, Mark R.; Heers, Susan T.; Rosekind, Mark R. (Technical Monitor)

1996-01-01

Automated decision aids and decision support systems have become essential tools in many high-tech environments. In aviation, for example, flight management systems computers not only fly the aircraft, but also calculate fuel efficient paths, detect and diagnose system malfunctions and abnormalities, and recommend or carry out decisions. Air Traffic Controllers will soon be utilizing decision support tools to help them predict and detect potential conflicts and to generate clearances. Other fields as disparate as nuclear power plants and medical diagnostics are similarly becoming more and more automated. Ideally, the combination of human decision maker and automated decision aid should result in a high-performing team, maximizing the advantages of additional cognitive and observational power in the decision-making process. In reality, however, the presence of these aids often short-circuits the way that even very experienced decision makers have traditionally handled tasks and made decisions, and introduces opportunities for new decision heuristics and biases. Results of recent research investigating the use of automated aids have indicated the presence of automation bias, that is, errors made when decision makers rely on automated cues as a heuristic replacement for vigilant information seeking and processing. Automation commission errors, i.e., errors made when decision makers inappropriately follow an automated directive, or automation omission errors, i.e., errors made when humans fail to take action or notice a problem because an automated aid fails to inform them, can result from this tendency. Evidence of the tendency to make automation-related omission and commission errors has been found in pilot self reports, in studies using pilots in flight simulations, and in non-flight decision making contexts with student samples. Considerable research has found that increasing social accountability can successfully ameliorate a broad array of cognitive biases and resultant errors. To what extent these effects generalize to performance situations is not yet empirically established. The two studies to be presented represent concurrent efforts, with student and professional pilot samples, to determine the effects of accountability pressures on automation bias and on the verification of the accurate functioning of automated aids. Students (Experiment 1) and commercial pilots (Experiment 2) performed simulated flight tasks using automated aids. In both studies, participants who perceived themselves as accountable for their strategies of interaction with the automation were significantly more likely to verify its correctness, and committed significantly fewer automation-related errors than those who did not report this perception.

Development of automated high throughput single molecular microfluidic detection platform for signal transduction analysis

NASA Astrophysics Data System (ADS)

Huang, Po-Jung; Baghbani Kordmahale, Sina; Chou, Chao-Kai; Yamaguchi, Hirohito; Hung, Mien-Chie; Kameoka, Jun

2016-03-01

Signal transductions including multiple protein post-translational modifications (PTM), protein-protein interactions (PPI), and protein-nucleic acid interaction (PNI) play critical roles for cell proliferation and differentiation that are directly related to the cancer biology. Traditional methods, like mass spectrometry, immunoprecipitation, fluorescence resonance energy transfer, and fluorescence correlation spectroscopy require a large amount of sample and long processing time. "microchannel for multiple-parameter analysis of proteins in single-complex (mMAPS)"we proposed can reduce the process time and sample volume because this system is composed by microfluidic channels, fluorescence microscopy, and computerized data analysis. In this paper, we will present an automated mMAPS including integrated microfluidic device, automated stage and electrical relay for high-throughput clinical screening. Based on this result, we estimated that this automated detection system will be able to screen approximately 150 patient samples in a 24-hour period, providing a practical application to analyze tissue samples in a clinical setting.

Automated detection system of single nucleotide polymorphisms using two kinds of functional magnetic nanoparticles

NASA Astrophysics Data System (ADS)

Liu, Hongna; Li, Song; Wang, Zhifei; Li, Zhiyang; Deng, Yan; Wang, Hua; Shi, Zhiyang; He, Nongyue

2008-11-01

Single nucleotide polymorphisms (SNPs) comprise the most abundant source of genetic variation in the human genome wide codominant SNPs identification. Therefore, large-scale codominant SNPs identification, especially for those associated with complex diseases, has induced the need for completely high-throughput and automated SNP genotyping method. Herein, we present an automated detection system of SNPs based on two kinds of functional magnetic nanoparticles (MNPs) and dual-color hybridization. The amido-modified MNPs (NH 2-MNPs) modified with APTES were used for DNA extraction from whole blood directly by electrostatic reaction, and followed by PCR, was successfully performed. Furthermore, biotinylated PCR products were captured on the streptavidin-coated MNPs (SA-MNPs) and interrogated by hybridization with a pair of dual-color probes to determine SNP, then the genotype of each sample can be simultaneously identified by scanning the microarray printed with the denatured fluorescent probes. This system provided a rapid, sensitive and highly versatile automated procedure that will greatly facilitate the analysis of different known SNPs in human genome.

Breast cancer knowledge, attitudes, and early detection practices in United States-Mexico border Latinas.

PubMed

Banegas, Matthew P; Bird, Yelena; Moraros, John; King, Sasha; Prapsiri, Surasri; Thompson, Beti

2012-01-01

Evidence suggests Latinas residing along the United States-Mexico border face higher breast cancer mortality rates compared to Latinas in the interior of either country. The purpose of this study was to investigate breast cancer knowledge, attitudes, and use of breast cancer preventive screening among U.S. Latina and Mexican women residing along the U.S.-Mexico border. For this binational cross-sectional study, 265 participants completed an interviewer-administered questionnaire that obtained information on sociodemographic characteristics, knowledge, attitudes, family history, and screening practices. Differences between Mexican (n=128) and U.S. Latina (n=137) participants were assessed by Pearson's chi-square, Fischer's exact test, t tests, and multivariate regression analyses. U.S. Latinas had significantly increased odds of having ever received a mammogram/breast ultrasound (adjusted odds ratio [OR]=2.95) and clinical breast examination (OR=2.67) compared to Mexican participants. A significantly greater proportion of Mexican women had high knowledge levels (54.8%) compared to U.S. Latinas (45.2%, p<0.05). Age, education, and insurance status were significantly associated with breast cancer screening use. Despite having higher levels of breast cancer knowledge than U.S. Latinas, Mexican women along the U.S.-Mexico border are not receiving the recommended breast cancer screening procedures. Although U.S. border Latinas had higher breast cancer screening levels than their Mexican counterparts, these levels are lower than those seen among the general U.S. Latina population. Our findings underscore the lack of access to breast cancer prevention screening services and emphasize the need to ensure that existing breast cancer screening programs are effective in reaching women along the U.S.-Mexico border.

Breast Cancer Knowledge, Attitudes, and Early Detection Practices in United States-Mexico Border Latinas

PubMed Central

Bird, Yelena; Moraros, John; King, Sasha; Prapsiri, Surasri; Thompson, Beti

2012-01-01

Abstract Introduction Evidence suggests Latinas residing along the United States-Mexico border face higher breast cancer mortality rates compared to Latinas in the interior of either country. The purpose of this study was to investigate breast cancer knowledge, attitudes, and use of breast cancer preventive screening among U.S. Latina and Mexican women residing along the U.S.-Mexico border. Methods For this binational cross-sectional study, 265 participants completed an interviewer-administered questionnaire that obtained information on sociodemographic characteristics, knowledge, attitudes, family history, and screening practices. Differences between Mexican (n=128) and U.S. Latina (n=137) participants were assessed by Pearson's chi-square, Fischer's exact test, t tests, and multivariate regression analyses. Results U.S. Latinas had significantly increased odds of having ever received a mammogram/breast ultrasound (adjusted odds ratio [OR]=2.95) and clinical breast examination (OR=2.67) compared to Mexican participants. A significantly greater proportion of Mexican women had high knowledge levels (54.8%) compared to U.S. Latinas (45.2%, p<0.05). Age, education, and insurance status were significantly associated with breast cancer screening use. Conclusions Despite having higher levels of breast cancer knowledge than U.S. Latinas, Mexican women along the U.S.-Mexico border are not receiving the recommended breast cancer screening procedures. Although U.S. border Latinas had higher breast cancer screening levels than their Mexican counterparts, these levels are lower than those seen among the general U.S. Latina population. Our findings underscore the lack of access to breast cancer prevention screening services and emphasize the need to ensure that existing breast cancer screening programs are effective in reaching women along the U.S.-Mexico border. PMID:21970564

Phenotyping for patient safety: algorithm development for electronic health record based automated adverse event and medical error detection in neonatal intensive care.

PubMed

Li, Qi; Melton, Kristin; Lingren, Todd; Kirkendall, Eric S; Hall, Eric; Zhai, Haijun; Ni, Yizhao; Kaiser, Megan; Stoutenborough, Laura; Solti, Imre

2014-01-01

Although electronic health records (EHRs) have the potential to provide a foundation for quality and safety algorithms, few studies have measured their impact on automated adverse event (AE) and medical error (ME) detection within the neonatal intensive care unit (NICU) environment. This paper presents two phenotyping AE and ME detection algorithms (ie, IV infiltrations, narcotic medication oversedation and dosing errors) and describes manual annotation of airway management and medication/fluid AEs from NICU EHRs. From 753 NICU patient EHRs from 2011, we developed two automatic AE/ME detection algorithms, and manually annotated 11 classes of AEs in 3263 clinical notes. Performance of the automatic AE/ME detection algorithms was compared to trigger tool and voluntary incident reporting results. AEs in clinical notes were double annotated and consensus achieved under neonatologist supervision. Sensitivity, positive predictive value (PPV), and specificity are reported. Twelve severe IV infiltrates were detected. The algorithm identified one more infiltrate than the trigger tool and eight more than incident reporting. One narcotic oversedation was detected demonstrating 100% agreement with the trigger tool. Additionally, 17 narcotic medication MEs were detected, an increase of 16 cases over voluntary incident reporting. Automated AE/ME detection algorithms provide higher sensitivity and PPV than currently used trigger tools or voluntary incident-reporting systems, including identification of potential dosing and frequency errors that current methods are unequipped to detect. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

GC13I-0860: An Assessment of Surface Water Detection Methods for the Tahoua Region, Niger

NASA Technical Reports Server (NTRS)

Herndon, Kelsey E.; Muench, Rebekke; Cherrington, Emil; Griffin, Robert

2017-01-01

The recent release of several global surface water datasets derived from remotely sensed data has allowed for unprecedented analysis of the earth's hydrologic processes at a global scale. However, some of these datasets fail to identify important sources of surface water, especially small ponds, in the Sahel, an arid region of Africa that forms a border zone between the Sahara Desert to the north, and the savannah to the south. These ponds may seem insignificant in the context of wider, global-scale hydrologic processes, but smaller sources of water are important for local and regional hydrologic assessments. Particularly, these smaller water bodies are significant sources of hydration and irrigation for nomadic pastoralists and smallholder farmers throughout the Sahel. For this study, several methods of identifying surface water from Landsat 8 OLI, Sentinel 1 SAR, Sentinel 2 MSI, and Planet Dove data were compared to determine the most effective means of delineating these features in the Tahoua Region of Niger. The Automated Water Extraction Index (AWEInsh) had the best performance when validated against very high resolution Digital Globe imagery, with an overall accuracy of 98.6%. This study reiterates the importance of region-specific algorithms and suggests that the AWEInsh method may be the best for delineating surface water in the Sahelian ecozone, likely due to the nature of the exposed geology and lack of dense green vegetation.

Automated detection of jet contrails using the AVHRR split window

NASA Technical Reports Server (NTRS)

Engelstad, M.; Sengupta, S. K.; Lee, T.; Welch, R. M.

1992-01-01

This paper investigates the automated detection of jet contrails using data from the Advanced Very High Resolution Radiometer. A preliminary algorithm subtracts the 11.8-micron image from the 10.8-micron image, creating a difference image on which contrails are enhanced. Then a three-stage algorithm searches the difference image for the nearly-straight line segments which characterize contrails. First, the algorithm searches for elevated, linear patterns called 'ridges'. Second, it applies a Hough transform to the detected ridges to locate nearly-straight lines. Third, the algorithm determines which of the nearly-straight lines are likely to be contrails. The paper applies this technique to several test scenes.

[Advances in automatic detection technology for images of thin blood film of malaria parasite].

PubMed

Juan-Sheng, Zhang; Di-Qiang, Zhang; Wei, Wang; Xiao-Guang, Wei; Zeng-Guo, Wang

2017-05-05

This paper reviews the computer vision and image analysis studies aiming at automated diagnosis or screening of malaria in microscope images of thin blood film smears. On the basis of introducing the background and significance of automatic detection technology, the existing detection technologies are summarized and divided into several steps, including image acquisition, pre-processing, morphological analysis, segmentation, count, and pattern classification components. Then, the principles and implementation methods of each step are given in detail. In addition, the promotion and application in automatic detection technology of thick blood film smears are put forwarded as questions worthy of study, and a perspective of the future work for realization of automated microscopy diagnosis of malaria is provided.

Automation based on knowledge modeling theory and its applications in engine diagnostic systems using Space Shuttle Main Engine vibrational data. M.S. Thesis

NASA Technical Reports Server (NTRS)

Kim, Jonnathan H.

1995-01-01

Humans can perform many complicated tasks without explicit rules. This inherent and advantageous capability becomes a hurdle when a task is to be automated. Modern computers and numerical calculations require explicit rules and discrete numerical values. In order to bridge the gap between human knowledge and automating tools, a knowledge model is proposed. Knowledge modeling techniques are discussed and utilized to automate a labor and time intensive task of detecting anomalous bearing wear patterns in the Space Shuttle Main Engine (SSME) High Pressure Oxygen Turbopump (HPOTP).

Automated Wildfire Detection Through Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Miller, Jerry; Borne, Kirk; Thomas, Brian; Huang, Zhenping; Chi, Yuechen

2005-01-01

We have tested and deployed Artificial Neural Network (ANN) data mining techniques to analyze remotely sensed multi-channel imaging data from MODIS, GOES, and AVHRR. The goal is to train the ANN to learn the signatures of wildfires in remotely sensed data in order to automate the detection process. We train the ANN using the set of human-detected wildfires in the U.S., which are provided by the Hazard Mapping System (HMS) wildfire detection group at NOAA/NESDIS. The ANN is trained to mimic the behavior of fire detection algorithms and the subjective decision- making by N O M HMS Fire Analysts. We use a local extremum search in order to isolate fire pixels, and then we extract a 7x7 pixel array around that location in 3 spectral channels. The corresponding 147 pixel values are used to populate a 147-dimensional input vector that is fed into the ANN. The ANN accuracy is tested and overfitting is avoided by using a subset of the training data that is set aside as a test data set. We have achieved an automated fire detection accuracy of 80-92%, depending on a variety of ANN parameters and for different instrument channels among the 3 satellites. We believe that this system can be deployed worldwide or for any region to detect wildfires automatically in satellite imagery of those regions. These detections can ultimately be used to provide thermal inputs to climate models.

An Automated Self-Learning Quantification System to Identify Visible Areas in Capsule Endoscopy Images.

PubMed

Hashimoto, Shinichi; Ogihara, Hiroyuki; Suenaga, Masato; Fujita, Yusuke; Terai, Shuji; Hamamoto, Yoshihiko; Sakaida, Isao

2017-08-01

Visibility in capsule endoscopic images is presently evaluated through intermittent analysis of frames selected by a physician. It is thus subjective and not quantitative. A method to automatically quantify the visibility on capsule endoscopic images has not been reported. Generally, when designing automated image recognition programs, physicians must provide a training image; this process is called supervised learning. We aimed to develop a novel automated self-learning quantification system to identify visible areas on capsule endoscopic images. The technique was developed using 200 capsule endoscopic images retrospectively selected from each of three patients. The rate of detection of visible areas on capsule endoscopic images between a supervised learning program, using training images labeled by a physician, and our novel automated self-learning program, using unlabeled training images without intervention by a physician, was compared. The rate of detection of visible areas was equivalent for the supervised learning program and for our automatic self-learning program. The visible areas automatically identified by self-learning program correlated to the areas identified by an experienced physician. We developed a novel self-learning automated program to identify visible areas in capsule endoscopic images.

Radioiodine therapy

MedlinePlus

... 3 days after treatment, you should: Limit your time in public places Not travel by airplane or use public transportation (you may set off the radiation detection machines in airports or at border ... the toilet 2 to 3 times after use For about 5 or more days ...

Human-system Interfaces to Automatic Systems: Review Guidance and Technical Basis

DOE Office of Scientific and Technical Information (OSTI.GOV)

OHara, J.M.; Higgins, J.C.

Automation has become ubiquitous in modern complex systems and commercial nuclear power plants are no exception. Beyond the control of plant functions and systems, automation is applied to a wide range of additional functions including monitoring and detection, situation assessment, response planning, response implementation, and interface management. Automation has become a 'team player' supporting plant personnel in nearly all aspects of plant operation. In light of the increasing use and importance of automation in new and future plants, guidance is needed to enable the NRC staff to conduct safety reviews of the human factors engineering (HFE) aspects of modern automation.more » The objective of the research described in this report was to develop guidance for reviewing the operator's interface with automation. We first developed a characterization of the important HFE aspects of automation based on how it is implemented in current systems. The characterization included five dimensions: Level of automation, function of automation, modes of automation, flexibility of allocation, and reliability of automation. Next, we reviewed literature pertaining to the effects of these aspects of automation on human performance and the design of human-system interfaces (HSIs) for automation. Then, we used the technical basis established by the literature to develop design review guidance. The guidance is divided into the following seven topics: Automation displays, interaction and control, automation modes, automation levels, adaptive automation, error tolerance and failure management, and HSI integration. In addition, we identified insights into the automaton design process, operator training, and operations.« less

Visual texture for automated characterisation of geological features in borehole televiewer imagery

NASA Astrophysics Data System (ADS)

Al-Sit, Waleed; Al-Nuaimy, Waleed; Marelli, Matteo; Al-Ataby, Ali

2015-08-01

Detailed characterisation of the structure of subsurface fractures is greatly facilitated by digital borehole logging instruments, the interpretation of which is typically time-consuming and labour-intensive. Despite recent advances towards autonomy and automation, the final interpretation remains heavily dependent on the skill, experience, alertness and consistency of a human operator. Existing computational tools fail to detect layers between rocks that do not exhibit distinct fracture boundaries, and often struggle characterising cross-cutting layers and partial fractures. This paper presents a novel approach to the characterisation of planar rock discontinuities from digital images of borehole logs. Multi-resolution texture segmentation and pattern recognition techniques utilising Gabor filters are combined with an iterative adaptation of the Hough transform to enable non-distinct, partial, distorted and steep fractures and layers to be accurately identified and characterised in a fully automated fashion. This approach has successfully detected fractures and layers with high detection accuracy and at a relatively low computational cost.

Automated exterior inspection of an aircraft with a pan-tilt-zoom camera mounted on a mobile robot

NASA Astrophysics Data System (ADS)

Jovančević, Igor; Larnier, Stanislas; Orteu, Jean-José; Sentenac, Thierry

2015-11-01

This paper deals with an automated preflight aircraft inspection using a pan-tilt-zoom camera mounted on a mobile robot moving autonomously around the aircraft. The general topic is image processing framework for detection and exterior inspection of different types of items, such as closed or unlatched door, mechanical defect on the engine, the integrity of the empennage, or damage caused by impacts or cracks. The detection step allows to focus on the regions of interest and point the camera toward the item to be checked. It is based on the detection of regular shapes, such as rounded corner rectangles, circles, and ellipses. The inspection task relies on clues, such as uniformity of isolated image regions, convexity of segmented shapes, and periodicity of the image intensity signal. The approach is applied to the inspection of four items of Airbus A320: oxygen bay handle, air-inlet vent, static ports, and fan blades. The results are promising and demonstrate the feasibility of an automated exterior inspection.

An automated detection for axonal boutons in vivo two-photon imaging of mouse

NASA Astrophysics Data System (ADS)

Li, Weifu; Zhang, Dandan; Xie, Qiwei; Chen, Xi; Han, Hua

2017-02-01

Activity-dependent changes in the synaptic connections of the brain are tightly related to learning and memory. Previous studies have shown that essentially all new synaptic contacts were made by adding new partners to existing synaptic elements. To further explore synaptic dynamics in specific pathways, concurrent imaging of pre and postsynaptic structures in identified connections is required. Consequently, considerable attention has been paid for the automated detection of axonal boutons. Different from most previous methods proposed in vitro data, this paper considers a more practical case in vivo neuron images which can provide real time information and direct observation of the dynamics of a disease process in mouse. Additionally, we present an automated approach for detecting axonal boutons by starting with deconvolving the original images, then thresholding the enhanced images, and reserving the regions fulfilling a series of criteria. Experimental result in vivo two-photon imaging of mouse demonstrates the effectiveness of our proposed method.

Enhancing Time-Series Detection Algorithms for Automated Biosurveillance

PubMed Central

Burkom, Howard; Xing, Jian; English, Roseanne; Bloom, Steven; Cox, Kenneth; Pavlin, Julie A.

2009-01-01

BioSense is a US national system that uses data from health information systems for automated disease surveillance. We studied 4 time-series algorithm modifications designed to improve sensitivity for detecting artificially added data. To test these modified algorithms, we used reports of daily syndrome visits from 308 Department of Defense (DoD) facilities and 340 hospital emergency departments (EDs). At a constant alert rate of 1%, sensitivity was improved for both datasets by using a minimum standard deviation (SD) of 1.0, a 14–28 day baseline duration for calculating mean and SD, and an adjustment for total clinic visits as a surrogate denominator. Stratifying baseline days into weekdays versus weekends to account for day-of-week effects increased sensitivity for the DoD data but not for the ED data. These enhanced methods may increase sensitivity without increasing the alert rate and may improve the ability to detect outbreaks by using automated surveillance system data. PMID:19331728

Synthesis of visibility detection systems.

DOT National Transportation Integrated Search

2012-10-01

Visibility is a critical component to the task of driving on all types of roads. The visibility detection and warning systems provide real-time, automated detection as well as appropriate responses to counteract reduced visibility conditions due to f...

Brown Marmorated Stink Bug (Hemiptera: Pentatomidae) Infestations in Tree Borders and Subsequent Patterns of Abundance in Soybean Fields.

PubMed

Aigner, B L; Kuhar, T P; Herbert, D A; Brewster, C C; Hogue, J W; Aigner, J D

2017-04-01

The invasive brown marmorated stink bug, Halyomorpha halys (Stål) (Hemiptera: Pentatomidae), is an important pest of soybean (Glycine max L. Merr.) in the Mid-Atlantic United States. In order to assess the influence of nonmanaged wooded borders on H. halys infestation patterns in soybean, 12 soybean fields in Orange and Madison Counties, VA, were sampled each week from July to October in 2013 or 2014 for H. halys. At each location, five 2-min visual counts of H. halys life stages were made on tree of heaven (Ailanthus altissima Mill.) and other favorable host trees along a wooded border, on the adjacent soybean edge, 15 m into the soybean field, and 30 m into the field. Seasonal data showed a clear trend at all locations of H. halys densities building up on A. altissima-dominated wooded borders in July, then, gradually moving into adjacent soybean field edges later in the summer. Halyomorpha halys did not move far from the invading field edge, with approximately half as many bugs being present at 15 m into the field and very few being detected 30 m into the field. These results have implications for continued monitoring and management using field border sprays, particularly on edges adjacent to woods. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Automated pattern analysis: A newsilent partner in insect acoustic detection studies

USDA-ARS?s Scientific Manuscript database

This seminar reviews methods that have been developed for automated analysis of field-collected sounds used to estimate pest populations and guide insect pest management decisions. Several examples are presented of successful usage of acoustic technology to map insect distributions in field environ...

Automated inspection of bread and loaves

NASA Astrophysics Data System (ADS)

Batchelor, Bruce G.

1993-08-01

The prospects for building practical automated inspection machines, capable of detecting the following faults in ordinary, everyday loaves are reviewed: (1) foreign bodies, using X-rays, (2) texture changes, using glancing illumination, mathematical morphology and Neural Net learning techniques, and (3) shape deformations, using structured lighting and simple geometry.

Automated volumetric segmentation of retinal fluid on optical coherence tomography

PubMed Central

Wang, Jie; Zhang, Miao; Pechauer, Alex D.; Liu, Liang; Hwang, Thomas S.; Wilson, David J.; Li, Dengwang; Jia, Yali

2016-01-01

We propose a novel automated volumetric segmentation method to detect and quantify retinal fluid on optical coherence tomography (OCT). The fuzzy level set method was introduced for identifying the boundaries of fluid filled regions on B-scans (x and y-axes) and C-scans (z-axis). The boundaries identified from three types of scans were combined to generate a comprehensive volumetric segmentation of retinal fluid. Then, artefactual fluid regions were removed using morphological characteristics and by identifying vascular shadowing with OCT angiography obtained from the same scan. The accuracy of retinal fluid detection and quantification was evaluated on 10 eyes with diabetic macular edema. Automated segmentation had good agreement with manual segmentation qualitatively and quantitatively. The fluid map can be integrated with OCT angiogram for intuitive clinical evaluation. PMID:27446676

Composite Wavelet Filters for Enhanced Automated Target Recognition

NASA Technical Reports Server (NTRS)

Chiang, Jeffrey N.; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2012-01-01

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low-resolution sonar and camera videos taken from unmanned vehicles. These sonar images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both sonar and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this paper.

Automated determination of arterial input function for DCE-MRI of the prostate

NASA Astrophysics Data System (ADS)

Zhu, Yingxuan; Chang, Ming-Ching; Gupta, Sandeep

2011-03-01

Prostate cancer is one of the commonest cancers in the world. Dynamic contrast enhanced MRI (DCE-MRI) provides an opportunity for non-invasive diagnosis, staging, and treatment monitoring. Quantitative analysis of DCE-MRI relies on determination of an accurate arterial input function (AIF). Although several methods for automated AIF detection have been proposed in literature, none are optimized for use in prostate DCE-MRI, which is particularly challenging due to large spatial signal inhomogeneity. In this paper, we propose a fully automated method for determining the AIF from prostate DCE-MRI. Our method is based on modeling pixel uptake curves as gamma variate functions (GVF). First, we analytically compute bounds on GVF parameters for more robust fitting. Next, we approximate a GVF for each pixel based on local time domain information, and eliminate the pixels with false estimated AIFs using the deduced upper and lower bounds. This makes the algorithm robust to signal inhomogeneity. After that, according to spatial information such as similarity and distance between pixels, we formulate the global AIF selection as an energy minimization problem and solve it using a message passing algorithm to further rule out the weak pixels and optimize the detected AIF. Our method is fully automated without training or a priori setting of parameters. Experimental results on clinical data have shown that our method obtained promising detection accuracy (all detected pixels inside major arteries), and a very good match with expert traced manual AIF.

A comparison of damage profiling of automated tap testers on aircraft CFRP panel

NASA Astrophysics Data System (ADS)

Mohd Aris, K. D.; Shariff, M. F.; Abd Latif, B. R.; Mohd Haris, M. Y.; Baidzawi, I. J.

2017-12-01

The use of composite materials nevertheless is getting more prominent. The combination of reinforcing fibers and matrices will produce the desired strength orientation, tailorability and not to mention the complex shape that is hard to form on metallic structure. The weight percentage of composite materials used in aerospace, civil, marine etc. has increased tremendously. Since composite are stacked together, the possibility of delamination and/disbond defects are highly present either in the monolithic or sandwich structures. Tap test is the cheapest form of nondestructive test to identify the presence of this damage. However, its inconsistency and wide area of coverage can reduce its effectivity since it is carried out manually. The indigenous automated tap tester known as KETOK was used to detect the damage due to trapped voids and air pockets. The mechanism of detection is through controlling the tapping on the surface automatically at a constant rate. Another manual tap tester RD-3 from Wichitech Industries Inc. was used as reference. The acquired data was translated into damage profiling and both results were compared. The results have shown that the indigenous automated tester can profile the damage better when compared with the existing tap tester. As a conclusion, the indigenous automated tap tester has a potential to be used as an IN-SITU damage detection tool to detect delamination and disbond damage on composite panel. However, more conclusive tests need to be done in order to make the unit available to conventional users.

Microbleed detection using automated segmentation (MIDAS): a new method applicable to standard clinical MR images.

PubMed

Seghier, Mohamed L; Kolanko, Magdalena A; Leff, Alexander P; Jäger, Hans R; Gregoire, Simone M; Werring, David J

2011-03-23

Cerebral microbleeds, visible on gradient-recalled echo (GRE) T2* MRI, have generated increasing interest as an imaging marker of small vessel diseases, with relevance for intracerebral bleeding risk or brain dysfunction. Manual rating methods have limited reliability and are time-consuming. We developed a new method for microbleed detection using automated segmentation (MIDAS) and compared it with a validated visual rating system. In thirty consecutive stroke service patients, standard GRE T2* images were acquired and manually rated for microbleeds by a trained observer. After spatially normalizing each patient's GRE T2* images into a standard stereotaxic space, the automated microbleed detection algorithm (MIDAS) identified cerebral microbleeds by explicitly incorporating an "extra" tissue class for abnormal voxels within a unified segmentation-normalization model. The agreement between manual and automated methods was assessed using the intraclass correlation coefficient (ICC) and Kappa statistic. We found that MIDAS had generally moderate to good agreement with the manual reference method for the presence of lobar microbleeds (Kappa = 0.43, improved to 0.65 after manual exclusion of obvious artefacts). Agreement for the number of microbleeds was very good for lobar regions: (ICC = 0.71, improved to ICC = 0.87). MIDAS successfully detected all patients with multiple (≥2) lobar microbleeds. MIDAS can identify microbleeds on standard MR datasets, and with an additional rapid editing step shows good agreement with a validated visual rating system. MIDAS may be useful in screening for multiple lobar microbleeds.

Rapid genotyping assays for the 4-base pair deletion of canine MDR1/ABCB1 gene and low frequency of the mutant allele in Border Collie dogs.

PubMed

Mizukami, Keijiro; Chang, Hye-Sook; Yabuki, Akira; Kawamichi, Takuji; Hossain, Mohammad A; Rahman, Mohammad M; Uddin, Mohammad M; Yamato, Osamu

2012-01-01

P-glycoprotein, encoded by the MDR1 or ABCB1 gene, is an integral component of the blood-brain barrier as an efflux pump for xenobiotics crucial in limiting drug uptake into the central nervous system. Dogs homozygous for a 4-base pair deletion of the canine MDR1 gene show altered expression or function of P-glycoprotein, resulting in neurotoxicosis after administration of the substrate drugs. In the present study, the usefulness of microchip electrophoresis for genotyping assays detecting this deletion mutation was evaluated. Mutagenically separated polymerase chain reaction (MS-PCR) and real-time PCR assays were newly developed and evaluated. Furthermore, a genotyping survey was carried out in a population of Border Collies dogs in Japan to determine the allele frequency in this breed. Microchip electrophoresis showed advantages in detection sensitivity and time saving over other modes of electrophoresis. The MS-PCR assay clearly discriminated all genotypes. Real-time PCR assay was most suitable for a large-scale survey due to its high throughput and rapidity. The genotyping survey demonstrated that the carrier and mutant allele frequencies were 0.49% and 0.25%, respectively, suggesting that the mutant allele frequency in Border Collies is markedly low compared to that in the susceptible dog breeds such as rough and smooth Collies.

Automation bias: decision making and performance in high-tech cockpits.

PubMed

Mosier, K L; Skitka, L J; Heers, S; Burdick, M

1997-01-01

Automated aids and decision support tools are rapidly becoming indispensable tools in high-technology cockpits and are assuming increasing control of"cognitive" flight tasks, such as calculating fuel-efficient routes, navigating, or detecting and diagnosing system malfunctions and abnormalities. This study was designed to investigate automation bias, a recently documented factor in the use of automated aids and decision support systems. The term refers to omission and commission errors resulting from the use of automated cues as a heuristic replacement for vigilant information seeking and processing. Glass-cockpit pilots flew flight scenarios involving automation events or opportunities for automation-related omission and commission errors. Although experimentally manipulated accountability demands did not significantly impact performance, post hoc analyses revealed that those pilots who reported an internalized perception of "accountability" for their performance and strategies of interaction with the automation were significantly more likely to double-check automated functioning against other cues and less likely to commit errors than those who did not share this perception. Pilots were also lilkely to erroneously "remember" the presence of expected cues when describing their decision-making processes.

Automated sinkhole detection using a DEM subsetting technique and fill tools at Mammoth Cave National Park

NASA Astrophysics Data System (ADS)

Wall, J.; Bohnenstiehl, D. R.; Levine, N. S.

2013-12-01

An automated workflow for sinkhole detection is developed using Light Detection and Ranging (Lidar) data from Mammoth Cave National Park (MACA). While the park is known to sit within a karst formation, the generally dense canopy cover and the size of the park (~53,000 acres) creates issues for sinkhole inventorying. Lidar provides a useful remote sensing technology for peering beneath the canopy in hard to reach areas of the park. In order to detect sinkholes, a subsetting technique is used to interpolate a Digital Elevation Model (DEM) thereby reducing edge effects. For each subset, standard GIS fill tools are used to fill depressions within the DEM. The initial DEM is then subtracted from the filled DEM resulting in detected depressions or sinkholes. Resulting depressions are then described in terms of size and geospatial trend.

ABO Mistyping of cis-AB Blood Group by the Automated Microplate Technique.

PubMed

Chun, Sejong; Ryu, Mi Ra; Cha, Seung-Yeon; Seo, Ji-Young; Cho, Duck

2018-01-01

The cis -AB phenotype, although rare, is the relatively most frequent of ABO subgroups in Koreans. To prevent ABO mistyping of cis -AB samples, our hospital has applied a combination of the manual tile method with automated devices. Herein, we report cases of ABO mistyping detected by the combination testing system. Cases that showed discrepant results by automated devices and the manual tile method were evaluated. These samples were also tested by the standard tube method. The automated devices used in this study were a QWALYS-3 and Galileo NEO. Exons 6 and 7 of the ABO gene were sequenced. 13 cases that had the cis -AB allele showed results suggestive of the cis -AB subgroup by manual methods, but were interpreted as AB by either automated device. This happened in 87.5% of these cases by QWALYS-3 and 70.0% by Galileo NEO. Genotyping results showed that 12 cases were ABO*cis-AB01/ABO*O01 or ABO*cis-AB01/ABO*O02 , and one case was ABO*cis-AB01/ ABO*A102. Cis -AB samples were mistyped as AB by the automated microplate technique in some cases. We suggest that the manual tile method can be a simple supplemental test for the detection of the cis -AB phenotype, especially in countries with relatively high cis- AB prevalence.

Classification methods to detect sleep apnea in adults based on respiratory and oximetry signals: a systematic review.

PubMed

Uddin, M B; Chow, C M; Su, S W

2018-03-26

Sleep apnea (SA), a common sleep disorder, can significantly decrease the quality of life, and is closely associated with major health risks such as cardiovascular disease, sudden death, depression, and hypertension. The normal diagnostic process of SA using polysomnography is costly and time consuming. In addition, the accuracy of different classification methods to detect SA varies with the use of different physiological signals. If an effective, reliable, and accurate classification method is developed, then the diagnosis of SA and its associated treatment will be time-efficient and economical. This study aims to systematically review the literature and present an overview of classification methods to detect SA using respiratory and oximetry signals and address the automated detection approach. Sixty-two included studies revealed the application of single and multiple signals (respiratory and oximetry) for the diagnosis of SA. Both airflow and oxygen saturation signals alone were effective in detecting SA in the case of binary decision-making, whereas multiple signals were good for multi-class detection. In addition, some machine learning methods were superior to the other classification methods for SA detection using respiratory and oximetry signals. To deal with the respiratory and oximetry signals, a good choice of classification method as well as the consideration of associated factors would result in high accuracy in the detection of SA. An accurate classification method should provide a high detection rate with an automated (independent of human action) analysis of respiratory and oximetry signals. Future high-quality automated studies using large samples of data from multiple patient groups or record batches are recommended.

Manual versus Automated Carotid Artery Plaque Component Segmentation in High and Lower Quality 3.0 Tesla MRI Scans

PubMed Central

Smits, Loek P.; van Wijk, Diederik F.; Duivenvoorden, Raphael; Xu, Dongxiang; Yuan, Chun; Stroes, Erik S.; Nederveen, Aart J.

2016-01-01

Purpose To study the interscan reproducibility of manual versus automated segmentation of carotid artery plaque components, and the agreement between both methods, in high and lower quality MRI scans. Methods 24 patients with 30–70% carotid artery stenosis were planned for 3T carotid MRI, followed by a rescan within 1 month. A multicontrast protocol (T1w,T2w, PDw and TOF sequences) was used. After co-registration and delineation of the lumen and outer wall, segmentation of plaque components (lipid-rich necrotic cores (LRNC) and calcifications) was performed both manually and automated. Scan quality was assessed using a visual quality scale. Results Agreement for the detection of LRNC (Cohen’s kappa (k) is 0.04) and calcification (k = 0.41) between both manual and automated segmentation methods was poor. In the high-quality scans (visual quality score ≥ 3), the agreement between manual and automated segmentation increased to k = 0.55 and k = 0.58 for, respectively, the detection of LRNC and calcification larger than 1 mm2. Both manual and automated analysis showed good interscan reproducibility for the quantification of LRNC (intraclass correlation coefficient (ICC) of 0.94 and 0.80 respectively) and calcified plaque area (ICC of 0.95 and 0.77, respectively). Conclusion Agreement between manual and automated segmentation of LRNC and calcifications was poor, despite a good interscan reproducibility of both methods. The agreement between both methods increased to moderate in high quality scans. These findings indicate that image quality is a critical determinant of the performance of both manual and automated segmentation of carotid artery plaque components. PMID:27930665

Remodeling of the transverse tubular system after myocardial infarction in rabbit correlates with local fibrosis: A potential role of biomechanics.

PubMed

Seidel, T; Sankarankutty, A C; Sachse, F B

2017-11-01

The transverse tubular system (t-system) of ventricular cardiomyocytes is essential for efficient excitation-contraction coupling. In cardiac diseases, such as heart failure, remodeling of the t-system contributes to reduced cardiac contractility. However, mechanisms of t-system remodeling are incompletely understood. Prior studies suggested an association with altered cardiac biomechanics and gene expression in disease. Since fibrosis may alter tissue biomechanics, we investigated the local microscopic association of t-system remodeling with fibrosis in a rabbit model of myocardial infarction (MI). Biopsies were taken from the MI border zone of 6 infarcted hearts and from 6 control hearts. Using confocal microscopy and automated image analysis, we quantified t-system integrity (I TT ) and the local fraction of extracellular matrix (f ECM ). In control, f ECM was 18 ± 0.3%. I TT was high and homogeneous (0.07 ± 0.006), and did not correlate with f ECM (R 2  = 0.05 ± 0.02). The MI border zone exhibited increased f ECM within 3 mm from the infarct scar (30 ± 3.5%, p < 0.01 vs control), indicating fibrosis. Myocytes in the MI border zone exhibited significant t-system remodeling, with dilated, sheet-like components, resulting in low I TT (0.03 ± 0.008, p < 0.001 vs control). While both f ECM and t-system remodeling decreased with infarct distance, I TT correlated better with decreasing f ECM (R 2  = 0.44) than with infarct distance (R 2  = 0.24, p < 0.05). Our results show that t-system remodeling in the rabbit MI border zone resembles a phenotype previously described in human heart failure. T-system remodeling correlated with the amount of local fibrosis, which is known to stiffen cardiac tissue, but was not found in regions without fibrosis. Thus, locally altered tissue mechanics may contribute to t-system remodeling. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of three automated nucleic acid extraction systems for identification of respiratory viruses in clinical specimens by multiplex real-time PCR.

PubMed

Kim, Yoonjung; Han, Mi-Soon; Kim, Juwon; Kwon, Aerin; Lee, Kyung-A

2014-01-01

A total of 84 nasopharyngeal swab specimens were collected from 84 patients. Viral nucleic acid was extracted by three automated extraction systems: QIAcube (Qiagen, Germany), EZ1 Advanced XL (Qiagen), and MICROLAB Nimbus IVD (Hamilton, USA). Fourteen RNA viruses and two DNA viruses were detected using the Anyplex II RV16 Detection kit (Seegene, Republic of Korea). The EZ1 Advanced XL system demonstrated the best analytical sensitivity for all the three viral strains. The nucleic acids extracted by EZ1 Advanced XL showed higher positive rates for virus detection than the others. Meanwhile, the MICROLAB Nimbus IVD system was comprised of fully automated steps from nucleic extraction to PCR setup function that could reduce human errors. For the nucleic acids recovered from nasopharyngeal swab specimens, the QIAcube system showed the fewest false negative results and the best concordance rate, and it may be more suitable for detecting various viruses including RNA and DNA virus strains. Each system showed different sensitivity and specificity for detection of certain viral pathogens and demonstrated different characteristics such as turnaround time and sample capacity. Therefore, these factors should be considered when new nucleic acid extraction systems are introduced to the laboratory.

Automated detection of masses on whole breast volume ultrasound scanner: false positive reduction using deep convolutional neural network

NASA Astrophysics Data System (ADS)

Hiramatsu, Yuya; Muramatsu, Chisako; Kobayashi, Hironobu; Hara, Takeshi; Fujita, Hiroshi

2017-03-01

Breast cancer screening with mammography and ultrasonography is expected to improve sensitivity compared with mammography alone, especially for women with dense breast. An automated breast volume scanner (ABVS) provides the operator-independent whole breast data which facilitate double reading and comparison with past exams, contralateral breast, and multimodality images. However, large volumetric data in screening practice increase radiologists' workload. Therefore, our goal is to develop a computer-aided detection scheme of breast masses in ABVS data for assisting radiologists' diagnosis and comparison with mammographic findings. In this study, false positive (FP) reduction scheme using deep convolutional neural network (DCNN) was investigated. For training DCNN, true positive and FP samples were obtained from the result of our initial mass detection scheme using the vector convergence filter. Regions of interest including the detected regions were extracted from the multiplanar reconstraction slices. We investigated methods to select effective FP samples for training the DCNN. Based on the free response receiver operating characteristic analysis, simple random sampling from the entire candidates was most effective in this study. Using DCNN, the number of FPs could be reduced by 60%, while retaining 90% of true masses. The result indicates the potential usefulness of DCNN for FP reduction in automated mass detection on ABVS images.

Rapid, automated, parallel quantitative immunoassays using highly integrated microfluidics and AlphaLISA

PubMed Central

Tak For Yu, Zeta; Guan, Huijiao; Ki Cheung, Mei; McHugh, Walker M.; Cornell, Timothy T.; Shanley, Thomas P.; Kurabayashi, Katsuo; Fu, Jianping

2015-01-01

Immunoassays represent one of the most popular analytical methods for detection and quantification of biomolecules. However, conventional immunoassays such as ELISA and flow cytometry, even though providing high sensitivity and specificity and multiplexing capability, can be labor-intensive and prone to human error, making them unsuitable for standardized clinical diagnoses. Using a commercialized no-wash, homogeneous immunoassay technology (‘AlphaLISA’) in conjunction with integrated microfluidics, herein we developed a microfluidic immunoassay chip capable of rapid, automated, parallel immunoassays of microliter quantities of samples. Operation of the microfluidic immunoassay chip entailed rapid mixing and conjugation of AlphaLISA components with target analytes before quantitative imaging for analyte detections in up to eight samples simultaneously. Aspects such as fluid handling and operation, surface passivation, imaging uniformity, and detection sensitivity of the microfluidic immunoassay chip using AlphaLISA were investigated. The microfluidic immunoassay chip could detect one target analyte simultaneously for up to eight samples in 45 min with a limit of detection down to 10 pg mL−1. The microfluidic immunoassay chip was further utilized for functional immunophenotyping to examine cytokine secretion from human immune cells stimulated ex vivo. Together, the microfluidic immunoassay chip provides a promising high-throughput, high-content platform for rapid, automated, parallel quantitative immunosensing applications. PMID:26074253

Directional analysis and filtering for dust storm detection in NOAA-AVHRR imagery

NASA Astrophysics Data System (ADS)

Janugani, S.; Jayaram, V.; Cabrera, S. D.; Rosiles, J. G.; Gill, T. E.; Rivera Rivera, N.

2009-05-01

In this paper, we propose spatio-spectral processing techniques for the detection of dust storms and automatically finding its transport direction in 5-band NOAA-AVHRR imagery. Previous methods that use simple band math analysis have produced promising results but have drawbacks in producing consistent results when low signal to noise ratio (SNR) images are used. Moreover, in seeking to automate the dust storm detection, the presence of clouds in the vicinity of the dust storm creates a challenge in being able to distinguish these two types of image texture. This paper not only addresses the detection of the dust storm in the imagery, it also attempts to find the transport direction and the location of the sources of the dust storm. We propose a spatio-spectral processing approach with two components: visualization and automation. Both approaches are based on digital image processing techniques including directional analysis and filtering. The visualization technique is intended to enhance the image in order to locate the dust sources. The automation technique is proposed to detect the transport direction of the dust storm. These techniques can be used in a system to provide timely warnings of dust storms or hazard assessments for transportation, aviation, environmental safety, and public health.

Automated detection of breast cancer in false-negative screening MRI studies from women at increased risk.

PubMed

Gubern-Mérida, Albert; Vreemann, Suzan; Martí, Robert; Melendez, Jaime; Lardenoije, Susanne; Mann, Ritse M; Karssemeijer, Nico; Platel, Bram

2016-02-01

To evaluate the performance of an automated computer-aided detection (CAD) system to detect breast cancers that were overlooked or misinterpreted in a breast MRI screening program for women at increased risk. We identified 40 patients that were diagnosed with breast cancer in MRI and had a prior MRI examination reported as negative available. In these prior examinations, 24 lesions could retrospectively be identified by two breast radiologists in consensus: 11 were scored as visible and 13 as minimally visible. Additionally, 120 normal scans were collected from 120 women without history of breast cancer or breast surgery participating in the same MRI screening program. A fully automated CAD system was applied to this dataset to detect malignant lesions. At 4 false-positives per normal case, the sensitivity for the detection of cancer lesions that were visible or minimally visible in retrospect in prior-negative examinations was 0.71 (95% CI=0.38-1.00) and 0.31 (0.07-0.59), respectively. A substantial proportion of cancers that were misinterpreted or overlooked in an MRI screening program was detected by a CAD system in prior-negative examinations. It has to be clarified with further studies if such a CAD system has an influence on the number of misinterpreted and overlooked cancers in clinical practice when results are given to a radiologist. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Sensitivity and specificity of automated detection of early repolarization in standard 12-lead electrocardiography.

PubMed

Kenttä, Tuomas; Porthan, Kimmo; Tikkanen, Jani T; Väänänen, Heikki; Oikarinen, Lasse; Viitasalo, Matti; Karanko, Hannu; Laaksonen, Maarit; Huikuri, Heikki V

2015-07-01

Early repolarization (ER) is defined as an elevation of the QRS-ST junction in at least two inferior or lateral leads of the standard 12-lead electrocardiogram (ECG). Our purpose was to create an algorithm for the automated detection and classification of ER. A total of 6,047 electrocardiograms were manually graded for ER by two experienced readers. The automated detection of ER was based on quantification of the characteristic slurring or notching in ER-positive leads. The ER detection algorithm was tested and its results were compared with manual grading, which served as the reference. Readers graded 183 ECGs (3.0%) as ER positive, of which the algorithm detected 176 recordings, resulting in sensitivity of 96.2%. Of the 5,864 ER-negative recordings, the algorithm classified 5,281 as negative, resulting in 90.1% specificity. Positive and negative predictive values for the algorithm were 23.2% and 99.9%, respectively, and its accuracy was 90.2%. Inferior ER was correctly detected in 84.6% and lateral ER in 98.6% of the cases. As the automatic algorithm has high sensitivity, it could be used as a prescreening tool for ER; only the electrocardiograms graded positive by the algorithm would be reviewed manually. This would reduce the need for manual labor by 90%. © 2014 Wiley Periodicals, Inc.

Cest Analysis: Automated Change Detection from Very-High Remote Sensing Images

NASA Astrophysics Data System (ADS)

Ehlers, M.; Klonus, S.; Jarmer, T.; Sofina, N.; Michel, U.; Reinartz, P.; Sirmacek, B.

2012-08-01

A fast detection, visualization and assessment of change in areas of crisis or catastrophes are important requirements for coordination and planning of help. Through the availability of new satellites and/or airborne sensors with very high spatial resolutions (e.g., WorldView, GeoEye) new remote sensing data are available for a better detection, delineation and visualization of change. For automated change detection, a large number of algorithms has been proposed and developed. From previous studies, however, it is evident that to-date no single algorithm has the potential for being a reliable change detector for all possible scenarios. This paper introduces the Combined Edge Segment Texture (CEST) analysis, a decision-tree based cooperative suite of algorithms for automated change detection that is especially designed for the generation of new satellites with very high spatial resolution. The method incorporates frequency based filtering, texture analysis, and image segmentation techniques. For the frequency analysis, different band pass filters can be applied to identify the relevant frequency information for change detection. After transforming the multitemporal images via a fast Fourier transform (FFT) and applying the most suitable band pass filter, different methods are available to extract changed structures: differencing and correlation in the frequency domain and correlation and edge detection in the spatial domain. Best results are obtained using edge extraction. For the texture analysis, different 'Haralick' parameters can be calculated (e.g., energy, correlation, contrast, inverse distance moment) with 'energy' so far providing the most accurate results. These algorithms are combined with a prior segmentation of the image data as well as with morphological operations for a final binary change result. A rule-based combination (CEST) of the change algorithms is applied to calculate the probability of change for a particular location. CEST was tested with high-resolution satellite images of the crisis areas of Darfur (Sudan). CEST results are compared with a number of standard algorithms for automated change detection such as image difference, image ratioe, principal component analysis, delta cue technique and post classification change detection. The new combined method shows superior results averaging between 45% and 15% improvement in accuracy.

Automated Detection of Craters in Martian Satellite Imagery Using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Norman, C. J.; Paxman, J.; Benedix, G. K.; Tan, T.; Bland, P. A.; Towner, M.

2018-04-01

Crater counting is used in determining surface age of planets. We propose improvements to martian Crater Detection Algorithms by implementing an end-to-end detection approach with the possibility of scaling the algorithm planet-wide.

Public Health Interventions and SARS Spread, 2003

PubMed Central

2004-01-01

The 2003 outbreak of severe acute respiratory syndrome (SARS) was contained largely through traditional public health interventions, such as finding and isolating case-patients, quarantining close contacts, and enhanced infection control. The independent effectiveness of measures to "increase social distance" and wearing masks in public places requires further evaluation. Limited data exist on the effectiveness of providing health information to travelers. Entry screening of travelers through health declarations or thermal scanning at international borders had little documented effect on detecting SARS cases; exit screening appeared slightly more effective. The value of border screening in deterring travel by ill persons and in building public confidence remains unquantified. Interventions to control global epidemics should be based on expert advice from the World Health Organization and national authorities. In the case of SARS, interventions at a country's borders should not detract from efforts to identify and isolate infected persons within the country, monitor or quarantine their contacts, and strengthen infection control in healthcare settings. PMID:15550198

Arbovirus Surveillance near the Mexico-U.S. Border: Isolation and Sequence Analysis of Chikungunya Virus from Patients with Dengue-like Symptoms in Reynosa, Tamaulipas.

PubMed

Laredo-Tiscareño, S Viridiana; Machain-Williams, Carlos; Rodríguez-Pérez, Mario A; Garza-Hernandez, Javier A; Doria-Cobos, Gloria L; Cetina-Trejo, Rosa C; Bacab-Cab, Lucio A; Tangudu, Chandra S; Charles, Jermilia; De Luna-Santillana, Erick J; Garcia-Rejon, Julian E; Blitvich, Bradley J

2018-05-14

A total of 1,090 residents of the city of Reynosa, Tamaulipas, on the Mexico-U.S. border presented at hospitals and clinics of the Secretariat of Health, Mexico, in 2015 with symptoms characteristic of dengue. Dengue virus (DENV) antigen was detected by enzyme-linked immunosorbent assay in acute sera from 134 (12.3%) patients. Sera from select patients ( N = 34) were also tested for chikungunya virus (CHIKV) RNA by quantitative reverse transcription-polymerase chain reaction. Thirteen (38.2%) patients, including five DENV antigen-positive patients, were positive. Sera from three CHIKV RNA-positive patients were further assayed by virus isolation in cell culture and CHIKV was recovered on each occasion. The genome of one isolate and structural genes of the other two isolates were sequenced. In conclusion, we present evidence of CHIKV and DENV coinfections in patients who live near the Mexico-U.S. border and provide the first genome sequence of a CHIKV isolate from northern Mexico.

Distribution of mosquitoes and mosquito-borne arboviruses in Yunnan Province near the China-Myanmar-Laos border.

PubMed

Wang, Jinglin; Zhang, Hailin; Sun, Xiaohong; Fu, Shihong; Wang, Huanqin; Feng, Yun; Wang, Huanyu; Tang, Qing; Liang, Guo-Dong

2011-05-01

Economic development and increased tourism in the southern region of Yunnan Province in China, adjacent to several countries in Southeast Asia, has increased the likelihood of import and export of vectors and vector-borne diseases. We report the results of surveillance of mosquitoes and mosquito-borne arboviruses along the border of China-Myanmar-Laos in 2005 and 2006, and information associating several arboviruses with infections and possibly disease in local human populations. Seventeen mosquito species representing four genera were obtained, and 14 strains of mosquito-borne viruses representing six viruses in five genera were isolated from Culex tritaeniorhynchus. In addition, IgM against Japanese encephalitis virus, Sindbis virus, Yunnan orbivirus and novel Banna virus was detected in acute-phase serum samples obtained from hospitalized patients with fever and encephalitis near the areas where the viruses were isolated. This investigation suggests that Japanese encephalitis virus, Sindbis virus, and lesser-known arboviruses circulate and may be infecting humans in the China-Myanmar-Laos border region.

Quantitative Indicators for Behaviour Drift Detection from Home Automation Data.

PubMed

Veronese, Fabio; Masciadri, Andrea; Comai, Sara; Matteucci, Matteo; Salice, Fabio

2017-01-01

Smart Homes diffusion provides an opportunity to implement elderly monitoring, extending seniors' independence and avoiding unnecessary assistance costs. Information concerning the inhabitant behaviour is contained in home automation data, and can be extracted by means of quantitative indicators. The application of such approach proves it can evidence behaviour changes.

A Framework for Automated Marmoset Vocalization Detection And Classification

DTIC Science & Technology

2016-09-08

recent push to automate vocalization monitoring in a range of mammals. Such efforts have been used to classify bird songs [11], African elephants [12... Elephant ( Loxodonta africana ) Vocalizations,” vol. 117, no. 2, pp. 956–963, 2005. [13] J. C. Brown, “Automatic classification of killer whale

MAVARIC - a comparison of automation-assisted and manual cervical screening: a randomised controlled trial.

PubMed

Kitchener, H C; Blanks, R; Cubie, H; Desai, M; Dunn, G; Legood, R; Gray, A; Sadique, Z; Moss, S

2011-01-01

The principal objective was to compare automation-assisted reading of cervical cytology with manual reading using the histological end point of cervical intraepithelial neoplasia grade II (CIN2) or worse (CIN2+). Secondary objectives included (i) an assessment of the slide ranking facility of the Becton Dickinson (BD) FocalPoint™ Slide Profiler (Becton Dickinson, Franklin Lakes, NJ, USA), especially 'No Further Review', (ii) a comparison of the two approved automated systems, the ThinPrep® Imaging System (Hologic, Bedford, MA, USA) and the BD FocalPoint Guided Screener Imaging System, and (iii) automated versus manual in terms of productivity and cost-effectiveness. A 1 : 2 randomised allocation of slides to either manual reading or automation-assisted paired with manual reading. Cytoscreeners were blinded to whether samples would be read only manually or manually paired with automated. Slide reading procedures followed real-life laboratory protocol to produce a final result and, for paired readings, the worse result determined the management. Costs per event were estimated and combined with productivity to produce a cost per slide, per woman and per CIN2+ and cervical intraepithelial neoplasia grade III (CIN3) or worse (CIN3+) lesion detected. Cost-effectiveness was estimated using cost per CIN2+ detected. Lifetime cost-effectiveness in terms of life-years and quality-adjusted life-years was estimated using a mathematical model. Liquid-based cytology samples were obtained in primary care, and a small number of abnormal samples were obtained from local colposcopy clinics, from different women, in order to enrich the proportion of abnormals. All of the samples were read in a single large service laboratory. Liquid residues used for human papillomavirus (HPV) triage were tested (with Hybrid Capture 2, Qiagen, Crawley, UK) in a specialist virology laboratory in Edinburgh, UK. Histopathology was read by a specialist gynaecological pathology team blinded to HPV results and type of reading. Samples were obtained from women aged 25-64 years undergoing primary cervical screening in Greater Manchester, UK, with small proportions from women outside this age range and from women undergoing colposcopy. The principal intervention was automation-assisted reading of cervical cytology slides which was paired with a manual reading of the same slide. Low-grade cytological abnormalities (borderline and mild dyskaryosis) were triaged with HPV testing to direct colposcopy referral. Women with high-grade cytology were referred for colposcopy and those with negative cytology were returned to recall. The principal outcome measure was the sensitivity of automation-assisted reading relative to manual for the detection of CIN2+. A secondary outcome measure was cost-effectiveness of each type of reading to detect CIN2+. The study was powered to detect a relative sensitivity difference equivalent to an absolute difference of 5%. The principal finding was that automated reading was 8% less sensitive relative to manual, 6.3% in absolute terms. 'No further review' was very reliable and, if restricted to routine screening samples, < 1% of CIN2+ would have been missed. Automated and manual were very similar in terms of cost-effectiveness despite a 60%-80% increase in productivity for automation-assisted reading. The significantly reduced sensitivity of automated reading, combined with uncertainty over cost-effectiveness, suggests no justification at present to recommend its introduction. The reliability of 'no further review' warrants further consideration as a means of saving staff time. Current Controlled Trials ISRCTN66377374. This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 15, No. 3. See the HTA programme website for further project information.

Can hyperspectral remote sensing detect species specific biochemicals?

USDA-ARS?s Scientific Manuscript database

Discrimination of a few plants scattered among many plants is a goal common to detection of agricultural weeds and invasive species. Detection of clandestinely grown Cannabis sativa L. is in many ways a special case of weed detection. Remote sensing technology provides an automated, computer based,...

Focused Screening and Treatment (FSAT): A PCR-Based Strategy to Detect Malaria Parasite Carriers and Contain Drug Resistant P. falciparum, Pailin, Cambodia

PubMed Central

Hoyer, Stefan; Nguon, Sokomar; Kim, Saorin; Habib, Najibullah; Khim, Nimol; Sum, Sarorn; Christophel, Eva-Maria; Bjorge, Steven; Thomson, Andrew; Kheng, Sim; Chea, Nguon; Yok, Sovann; Top, Samphornarann; Ros, Seyha; Sophal, Uth; Thompson, Michelle M.; Mellor, Steve; Ariey, Frédéric; Witkowski, Benoit; Yeang, Chhiang; Yeung, Shunmay; Duong, Socheat; Newman, Robert D.; Menard, Didier

2012-01-01

Recent studies have shown that Plasmodium falciparum malaria parasites in Pailin province, along the border between Thailand and Cambodia, have become resistant to artemisinin derivatives. To better define the epidemiology of P. falciparum populations and to assess the risk of the possible spread of these parasites outside Pailin, a new epidemiological tool named “Focused Screening and Treatment” (FSAT), based on active molecular detection of asymptomatic parasite carriers was introduced in 2010. Cross-sectional malariometric surveys using PCR were carried out in 20 out of 109 villages in Pailin province. Individuals detected as P. falciparum carriers were treated with atovaquone-proguanil combination plus a single dose of primaquine if the patient was non-G6PD deficient. Interviews were conducted to elicit history of cross-border travel that might contribute to the spread of artemisinin-resistant parasites. After directly observed treatment, patients were followed up and re-examined on day 7 and day 28. Among 6931 individuals screened, prevalence of P. falciparum carriers was less than 1%, of whom 96% were asymptomatic. Only 1.6% of the individuals had a travel history or plans to go outside Cambodia, with none of those tested being positive for P. falciparum. Retrospective analysis, using 2010 routine surveillance data, showed significant differences in the prevalence of asymptomatic carriers discovered by FSAT between villages classified as “high risk” and “low risk” based on malaria incidence data. All positive individuals treated and followed-up until day 28 were cured. No mutant-type allele related to atovaquone resistance was found. FSAT is a potentially useful tool to detect, treat and track clusters of asymptomatic carriers of P. falciparum along with providing valuable epidemiological information regarding cross-border movements of potential malaria parasite carriers and parasite gene flow. PMID:23049687

Automated Cell Detection and Morphometry on Growth Plate Images of Mouse Bone

PubMed Central

Ascenzi, Maria-Grazia; Du, Xia; Harding, James I; Beylerian, Emily N; de Silva, Brian M; Gross, Ben J; Kastein, Hannah K; Wang, Weiguang; Lyons, Karen M; Schaeffer, Hayden

2014-01-01

Microscopy imaging of mouse growth plates is extensively used in biology to understand the effect of specific molecules on various stages of normal bone development and on bone disease. Until now, such image analysis has been conducted by manual detection. In fact, when existing automated detection techniques were applied, morphological variations across the growth plate and heterogeneity of image background color, including the faint presence of cells (chondrocytes) located deeper in tissue away from the image’s plane of focus, and lack of cell-specific features, interfered with identification of cell. We propose the first method of automated detection and morphometry applicable to images of cells in the growth plate of long bone. Through ad hoc sequential application of the Retinex method, anisotropic diffusion and thresholding, our new cell detection algorithm (CDA) addresses these challenges on bright-field microscopy images of mouse growth plates. Five parameters, chosen by the user in respect of image characteristics, regulate our CDA. Our results demonstrate effectiveness of the proposed numerical method relative to manual methods. Our CDA confirms previously established results regarding chondrocytes’ number, area, orientation, height and shape of normal growth plates. Our CDA also confirms differences previously found between the genetic mutated mouse Smad1/5CKO and its control mouse on fluorescence images. The CDA aims to aid biomedical research by increasing efficiency and consistency of data collection regarding arrangement and characteristics of chondrocytes. Our results suggest that automated extraction of data from microscopy imaging of growth plates can assist in unlocking information on normal and pathological development, key to the underlying biological mechanisms of bone growth. PMID:25525552

Current automated 3D cell detection methods are not a suitable replacement for manual stereologic cell counting

PubMed Central

Schmitz, Christoph; Eastwood, Brian S.; Tappan, Susan J.; Glaser, Jack R.; Peterson, Daniel A.; Hof, Patrick R.

2014-01-01

Stereologic cell counting has had a major impact on the field of neuroscience. A major bottleneck in stereologic cell counting is that the user must manually decide whether or not each cell is counted according to three-dimensional (3D) stereologic counting rules by visual inspection within hundreds of microscopic fields-of-view per investigated brain or brain region. Reliance on visual inspection forces stereologic cell counting to be very labor-intensive and time-consuming, and is the main reason why biased, non-stereologic two-dimensional (2D) “cell counting” approaches have remained in widespread use. We present an evaluation of the performance of modern automated cell detection and segmentation algorithms as a potential alternative to the manual approach in stereologic cell counting. The image data used in this study were 3D microscopic images of thick brain tissue sections prepared with a variety of commonly used nuclear and cytoplasmic stains. The evaluation compared the numbers and locations of cells identified unambiguously and counted exhaustively by an expert observer with those found by three automated 3D cell detection algorithms: nuclei segmentation from the FARSIGHT toolkit, nuclei segmentation by 3D multiple level set methods, and the 3D object counter plug-in for ImageJ. Of these methods, FARSIGHT performed best, with true-positive detection rates between 38 and 99% and false-positive rates from 3.6 to 82%. The results demonstrate that the current automated methods suffer from lower detection rates and higher false-positive rates than are acceptable for obtaining valid estimates of cell numbers. Thus, at present, stereologic cell counting with manual decision for object inclusion according to unbiased stereologic counting rules remains the only adequate method for unbiased cell quantification in histologic tissue sections. PMID:24847213

Automated video-based detection of nocturnal convulsive seizures in a residential care setting.

PubMed

Geertsema, Evelien E; Thijs, Roland D; Gutter, Therese; Vledder, Ben; Arends, Johan B; Leijten, Frans S; Visser, Gerhard H; Kalitzin, Stiliyan N

2018-06-01

People with epilepsy need assistance and are at risk of sudden death when having convulsive seizures (CS). Automated real-time seizure detection systems can help alert caregivers, but wearable sensors are not always tolerated. We determined algorithm settings and investigated detection performance of a video algorithm to detect CS in a residential care setting. The algorithm calculates power in the 2-6 Hz range relative to 0.5-12.5 Hz range in group velocity signals derived from video-sequence optical flow. A detection threshold was found using a training set consisting of video-electroencephalogaphy (EEG) recordings of 72 CS. A test set consisting of 24 full nights of 12 new subjects in residential care and additional recordings of 50 CS selected randomly was used to estimate performance. All data were analyzed retrospectively. The start and end of CS (generalized clonic and tonic-clonic seizures) and other seizures considered desirable to detect (long generalized tonic, hyperkinetic, and other major seizures) were annotated. The detection threshold was set to the value that obtained 97% sensitivity in the training set. Sensitivity, latency, and false detection rate (FDR) per night were calculated in the test set. A seizure was detected when the algorithm output exceeded the threshold continuously for 2 seconds. With the detection threshold determined in the training set, all CS were detected in the test set (100% sensitivity). Latency was ≤10 seconds in 78% of detections. Three/five hyperkinetic and 6/9 other major seizures were detected. Median FDR was 0.78 per night and no false detections occurred in 9/24 nights. Our algorithm could improve safety unobtrusively by automated real-time detection of CS in video registrations, with an acceptable latency and FDR. The algorithm can also detect some other motor seizures requiring assistance. © 2018 The Authors. Epilepsia published by Wiley Periodicals, Inc. on behalf of International League Against Epilepsy.

Comparison of two drug safety signals in a pharmacovigilance data mining framework.

PubMed

Tubert-Bitter, Pascale; Bégaud, Bernard; Ahmed, Ismaïl

2016-04-01

Since adverse drug reactions are a major public health concern, early detection of drug safety signals has become a top priority for regulatory agencies and the pharmaceutical industry. Quantitative methods for analyzing spontaneous reporting material recorded in pharmacovigilance databases through data mining have been proposed in the last decades and are increasingly used to flag potential safety problems. While automated data mining is motivated by the usually huge size of pharmacovigilance databases, it does not systematically produce relevant alerts. Moreover, each detected signal requires appropriate assessment that may involve investigation of the whole therapeutic class. The goal of this article is to provide a methodology for comparing two detected signals. It is nested within the automated surveillance framework as (1) no extra information is required and (2) no simple inference on the actual risks can be extrapolated from spontaneous reporting data. We designed our methodology on the basis of two classical methods used for automated signal detection: the Bayesian Gamma Poisson Shrinker and the frequentist Proportional Reporting Ratio. A simulation study was conducted to assess the performances of both proposed methods. The latter were used to compare cardiovascular signals for two HIV treatments from the French pharmacovigilance database. © The Author(s) 2012.

Vision Marker-Based In Situ Examination of Bacterial Growth in Liquid Culture Media.

PubMed

Kim, Kyukwang; Choi, Duckyu; Lim, Hwijoon; Kim, Hyeongkeun; Jeon, Jessie S

2016-12-18

The detection of bacterial growth in liquid media is an essential process in determining antibiotic susceptibility or the level of bacterial presence for clinical or research purposes. We have developed a system, which enables simplified and automated detection using a camera and a striped pattern marker. The quantification of bacterial growth is possible as the bacterial growth in the culturing vessel blurs the marker image, which is placed on the back of the vessel, and the blurring results in a decrease in the high-frequency spectrum region of the marker image. The experiment results show that the FFT (fast Fourier transform)-based growth detection method is robust to the variations in the type of bacterial carrier and vessels ranging from the culture tubes to the microfluidic devices. Moreover, the automated incubator and image acquisition system are developed to be used as a comprehensive in situ detection system. We expect that this result can be applied in the automation of biological experiments, such as the Antibiotics Susceptibility Test or toxicity measurement. Furthermore, the simple framework of the proposed growth measurement method may be further utilized as an effective and convenient method for building point-of-care devices for developing countries.

[Algorithm of locally adaptive region growing based on multi-template matching applied to automated detection of hemorrhages].

PubMed

Gao, Wei-Wei; Shen, Jian-Xin; Wang, Yu-Liang; Liang, Chun; Zuo, Jing

2013-02-01

In order to automatically detect hemorrhages in fundus images, and develop an automated diabetic retinopathy screening system, a novel algorithm named locally adaptive region growing based on multi-template matching was established and studied. Firstly, spectral signature of major anatomical structures in fundus was studied, so that the right channel among RGB channels could be selected for different segmentation objects. Secondly, the fundus image was preprocessed by means of HSV brightness correction and contrast limited adaptive histogram equalization (CLAHE). Then, seeds of region growing were founded out by removing optic disc and vessel from the resulting image of normalized cross-correlation (NCC) template matching on the previous preprocessed image with several templates. Finally, locally adaptive region growing segmentation was used to find out the exact contours of hemorrhages, and the automated detection of the lesions was accomplished. The approach was tested on 90 different resolution fundus images with variable color, brightness and quality. Results suggest that the approach could fast and effectively detect hemorrhages in fundus images, and it is stable and robust. As a result, the approach can meet the clinical demands.

Advances in algorithm fusion for automated sea mine detection and classification

NASA Astrophysics Data System (ADS)

Dobeck, Gerald J.; Cobb, J. Tory

2002-11-01

Along with other sensors, the Navy uses high-resolution sonar to detect and classify sea mines in mine-hunting operations. Scientists and engineers have devoted substantial effort to the development of automated detection and classification (D/C) algorithms for these high-resolution systems. Several factors spurred these efforts, including: (1) aids for operators to reduce work overload; (2) more optimal use of all available data; and (3) the introduction of unmanned minehunting systems. The environments where sea mines are typically laid (harbor areas, shipping lanes, and the littorals) give rise to many false alarms caused by natural, biologic, and manmade clutter. The objective of the automated D/C algorithms is to eliminate most of these false alarms while maintaining a very high probability of mine detection and classification (PdPc). In recent years, the benefits of fusing the outputs of multiple D/C algorithms (Algorithm Fusion) have been studied. To date, the results have been remarkable, including reliable robustness to new environments. In this paper a brief history of existing Algorithm Fusion technology and some techniques recently used to improve performance are presented. An exploration of new developments is presented in conclusion.

Automated attribution of remotely-sensed ecological disturbances using spatial and temporal characteristics of common disturbance classes.

NASA Astrophysics Data System (ADS)

Cooper, L. A.; Ballantyne, A.

2017-12-01

Forest disturbances are critical components of ecosystems. Knowledge of their prevalence and impacts is necessary to accurately describe forest health and ecosystem services through time. While there are currently several methods available to identify and describe forest disturbances, especially those which occur in North America, the process remains inefficient and inaccessible in many parts of the world. Here, we introduce a preliminary approach to streamline and automate both the detection and attribution of forest disturbances. We use a combination of the Breaks for Additive Season and Trend (BFAST) detection algorithm to detect disturbances in combination with supervised and unsupervised classification algorithms to attribute the detections to disturbance classes. Both spatial and temporal disturbance characteristics are derived and utilized for the goal of automating the disturbance attribution process. The resulting preliminary algorithm is applied to up-scaled (100m) Landsat data for several different ecosystems in North America, with varying success. Our results indicate that supervised classification is more reliable than unsupervised classification, but that limited training data are required for a region. Future work will improve the algorithm through refining and validating at sites within North America before applying this approach globally.

Understanding the Effect of Workload on Automation Use for Younger and Older Adults

PubMed Central

McBride, Sara E.; Rogers, Wendy A.; Fisk, Arthur D.

2018-01-01

Objective This study examined how individuals, younger and older, interacted with an imperfect automated system. The impact of workload on performance and automation use was also investigated. Background Automation is used in situations characterized by varying levels of workload. As automated systems spread to domains such as transportation and the home, a diverse population of users will interact with automation. Research is needed to understand how different segments of the population use automation. Method Workload was systematically manipulated to create three levels (low, moderate, high) in a dual-task scenario in which participants interacted with a 70% reliable automated aid. Two experiments were conducted to assess automation use for younger and older adults. Results Both younger and older adults relied on the automation more than they complied with it. Among younger adults, high workload led to poorer performance and higher compliance, even when that compliance was detrimental. Older adults’ performance was negatively affected by workload, but their compliance and reliance were unaffected. Conclusion Younger and older adults were both able to use and double-check an imperfect automated system. Workload affected how younger adults complied with automation, particularly with regard to detecting automation false alarms. Older adults tended to comply and rely at fairly high rates overall, and this did not change with increased workload. Application Training programs for imperfect automated systems should vary workload and provide feedback about error types, and strategies for identifying errors. The ability to identify automation errors varies across individuals, thereby necessitating training. PMID:22235529

Understanding the effect of workload on automation use for younger and older adults.

PubMed

McBride, Sara E; Rogers, Wendy A; Fisk, Arthur D

2011-12-01

This study examined how individuals, younger and older, interacted with an imperfect automated system. The impact of workload on performance and automation use was also investigated. Automation is used in situations characterized by varying levels of workload. As automated systems spread to domains such as transportation and the home, a diverse population of users will interact with automation. Research is needed to understand how different segments of the population use automation. Workload was systematically manipulated to create three levels (low, moderate, high) in a dual-task scenario in which participants interacted with a 70% reliable automated aid. Two experiments were conducted to assess automation use for younger and older adults. Both younger and older adults relied on the automation more than they complied with it. Among younger adults, high workload led to poorer performance and higher compliance, even when that compliance was detrimental. Older adults' performance was negatively affected by workload, but their compliance and reliance were unaffected. Younger and older adults were both able to use and double-check an imperfect automated system. Workload affected how younger adults complied with automation, particularly with regard to detecting automation false alarms. Older adults tended to comply and rely at fairly high rates overall, and this did not change with increased workload. Training programs for imperfect automated systems should vary workload and provide feedback about error types, and strategies for identifying errors. The ability to identify automation errors varies across individuals, thereby necessitating training.

Automated detection and segmentation of follicles in 3D ultrasound for assisted reproduction

NASA Astrophysics Data System (ADS)

Narayan, Nikhil S.; Sivanandan, Srinivasan; Kudavelly, Srinivas; Patwardhan, Kedar A.; Ramaraju, G. A.

2018-02-01

Follicle quantification refers to the computation of the number and size of follicles in 3D ultrasound volumes of the ovary. This is one of the key factors in determining hormonal dosage during female infertility treatments. In this paper, we propose an automated algorithm to detect and segment follicles in 3D ultrasound volumes of the ovary for quantification. In a first of its kind attempt, we employ noise-robust phase symmetry feature maps as likelihood function to perform mean-shift based follicle center detection. Max-flow algorithm is used for segmentation and gray weighted distance transform is employed for post-processing the results. We have obtained state-of-the-art results with a true positive detection rate of >90% on 26 3D volumes with 323 follicles.

Automated Microfluidic Filtration and Immunocytochemistry Detection System for Capture and Enumeration of Circulating Tumor Cells and Other Rare Cell Populations in Blood.

PubMed

Pugia, Michael; Magbanua, Mark Jesus M; Park, John W

2017-01-01

Isolation by size using a filter membrane offers an antigen-independent method for capturing rare cells present in blood of cancer patients. Multiple cell types, including circulating tumor cells (CTCs), captured on the filter membrane can be simultaneously identified via immunocytochemistry (ICC) analysis of specific cellular biomarkers. Here, we describe an automated microfluidic filtration method combined with a liquid handling system for sequential ICC assays to detect and enumerate non-hematologic rare cells in blood.

TreeRipper web application: towards a fully automated optical tree recognition software.

PubMed

Hughes, Joseph

2011-05-20

Relationships between species, genes and genomes have been printed as trees for over a century. Whilst this may have been the best format for exchanging and sharing phylogenetic hypotheses during the 20th century, the worldwide web now provides faster and automated ways of transferring and sharing phylogenetic knowledge. However, novel software is needed to defrost these published phylogenies for the 21st century. TreeRipper is a simple website for the fully-automated recognition of multifurcating phylogenetic trees (http://linnaeus.zoology.gla.ac.uk/~jhughes/treeripper/). The program accepts a range of input image formats (PNG, JPG/JPEG or GIF). The underlying command line c++ program follows a number of cleaning steps to detect lines, remove node labels, patch-up broken lines and corners and detect line edges. The edge contour is then determined to detect the branch length, tip label positions and the topology of the tree. Optical Character Recognition (OCR) is used to convert the tip labels into text with the freely available tesseract-ocr software. 32% of images meeting the prerequisites for TreeRipper were successfully recognised, the largest tree had 115 leaves. Despite the diversity of ways phylogenies have been illustrated making the design of a fully automated tree recognition software difficult, TreeRipper is a step towards automating the digitization of past phylogenies. We also provide a dataset of 100 tree images and associated tree files for training and/or benchmarking future software. TreeRipper is an open source project licensed under the GNU General Public Licence v3.

Automated quantification of neuronal networks and single-cell calcium dynamics using calcium imaging

PubMed Central

Patel, Tapan P.; Man, Karen; Firestein, Bonnie L.; Meaney, David F.

2017-01-01

Background Recent advances in genetically engineered calcium and membrane potential indicators provide the potential to estimate the activation dynamics of individual neurons within larger, mesoscale networks (100s–1000 +neurons). However, a fully integrated automated workflow for the analysis and visualization of neural microcircuits from high speed fluorescence imaging data is lacking. New method Here we introduce FluoroSNNAP, Fluorescence Single Neuron and Network Analysis Package. FluoroSNNAP is an open-source, interactive software developed in MATLAB for automated quantification of numerous biologically relevant features of both the calcium dynamics of single-cells and network activity patterns. FluoroSNNAP integrates and improves upon existing tools for spike detection, synchronization analysis, and inference of functional connectivity, making it most useful to experimentalists with little or no programming knowledge. Results We apply FluoroSNNAP to characterize the activity patterns of neuronal microcircuits undergoing developmental maturation in vitro. Separately, we highlight the utility of single-cell analysis for phenotyping a mixed population of neurons expressing a human mutant variant of the microtubule associated protein tau and wild-type tau. Comparison with existing method(s) We show the performance of semi-automated cell segmentation using spatiotemporal independent component analysis and significant improvement in detecting calcium transients using a template-based algorithm in comparison to peak-based or wavelet-based detection methods. Our software further enables automated analysis of microcircuits, which is an improvement over existing methods. Conclusions We expect the dissemination of this software will facilitate a comprehensive analysis of neuronal networks, promoting the rapid interrogation of circuits in health and disease. PMID:25629800

Isomorphic red blood cells using automated urine flow cytometry is a reliable method in diagnosis of bladder cancer.

PubMed

Muto, Satoru; Sugiura, Syo-Ichiro; Nakajima, Akiko; Horiuchi, Akira; Inoue, Masahiro; Saito, Keisuke; Isotani, Shuji; Yamaguchi, Raizo; Ide, Hisamitsu; Horie, Shigeo

2014-10-01

We aimed to identify patients with a chief complaint of hematuria who could safely avoid unnecessary radiation and instrumentation in the diagnosis of bladder cancer (BC), using automated urine flow cytometry to detect isomorphic red blood cells (RBCs) in urine. We acquired urine samples from 134 patients over the age of 35 years with a chief complaint of hematuria and a positive urine occult blood test or microhematuria. The data were analyzed using the UF-1000i (®) (Sysmex Co., Ltd., Kobe, Japan) automated urine flow cytometer to determine RBC morphology, which was classified as isomorphic or dysmorphic. The patients were divided into two groups (BC versus non-BC) for statistical analysis. Multivariate logistic regression analysis was used to determine the predictive value of flow cytometry versus urine cytology, the bladder tumor antigen test, occult blood in urine test, and microhematuria test. BC was confirmed in 26 of 134 patients (19.4 %). The area under the curve for RBC count using the automated urine flow cytometer was 0.94, representing the highest reference value obtained in this study. Isomorphic RBCs were detected in all patients in the BC group. On multivariate logistic regression analysis, only isomorphic RBC morphology was significantly predictive for BC (p < 0.001). Analytical parameters such as sensitivity, specificity, positive predictive value, and negative predictive value of isomorphic RBCs in urine were 100.0, 91.7, 74.3, and 100.0 %, respectively. Detection of urinary isomorphic RBCs using automated urine flow cytometry is a reliable method in the diagnosis of BC with hematuria.